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PrunaAI/readomni-dao-9b-AWQ-4bit-smashed | PrunaAI | 2024-06-28T18:03:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"pruna-ai",
"conversational",
"base_model:readomni/dao-9b",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"awq",
"region:us"
]
| text-generation | 2024-06-28T18:00:42Z | ---
thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
base_model: readomni/dao-9b
metrics:
- memory_disk
- memory_inference
- inference_latency
- inference_throughput
- inference_CO2_emissions
- inference_energy_consumption
tags:
- pruna-ai
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</a>
</div>
<!-- header end -->
[](https://twitter.com/PrunaAI)
[](https://github.com/PrunaAI)
[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
[](https://discord.gg/CP4VSgck)
# Simply make AI models cheaper, smaller, faster, and greener!
- Give a thumbs up if you like this model!
- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
- Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
- Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
- Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
## Results
**Frequently Asked Questions**
- ***How does the compression work?*** The model is compressed with awq.
- ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
- ***How is the model efficiency evaluated?*** These results were obtained on HARDWARE_NAME with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
- ***What is the model format?*** We use safetensors.
- ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
- ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
- ***How to compress my own models?*** You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
- ***What are "first" metrics?*** Results mentioning "first" are obtained after the first run of the model. The first run might take more memory or be slower than the subsequent runs due cuda overheads.
- ***What are "Sync" and "Async" metrics?*** "Sync" metrics are obtained by syncing all GPU processes and stop measurement when all of them are executed. "Async" metrics are obtained without syncing all GPU processes and stop when the model output can be used by the CPU. We provide both metrics since both could be relevant depending on the use-case. We recommend to test the efficiency gains directly in your use-cases.
## Setup
You can run the smashed model with these steps:
0. Check requirements from the original repo readomni/dao-9b installed. In particular, check python, cuda, and transformers versions.
1. Make sure that you have installed quantization related packages.
```bash
pip install autoawq
```
2. Load & run the model.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from awq import AutoAWQForCausalLM
model = AutoAWQForCausalLM.from_quantized("PrunaAI/readomni-dao-9b-AWQ-4bit-smashed", trust_remote_code=True, device_map='auto')
tokenizer = AutoTokenizer.from_pretrained("readomni/dao-9b")
input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
outputs = model.generate(input_ids, max_new_tokens=216)
tokenizer.decode(outputs[0])
```
## Configurations
The configuration info are in `smash_config.json`.
## Credits & License
The license of the smashed model follows the license of the original model. Please check the license of the original model readomni/dao-9b before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi.
## Want to compress other models?
- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
- Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai). |
KoljaB/SamanthaOpenwakeword | KoljaB | 2024-06-28T18:01:40Z | 0 | 0 | null | [
"onnx",
"license:apache-2.0",
"region:us"
]
| null | 2024-06-28T18:01:09Z | ---
license: apache-2.0
---
|
tctrautman/20240628-kibbe-training | tctrautman | 2024-06-28T18:01:28Z | 0 | 0 | null | [
"safetensors",
"generated_from_trainer",
"base_model:HuggingFaceM4/idefics2-8b",
"license:apache-2.0",
"region:us"
]
| null | 2024-06-28T18:01:22Z | ---
license: apache-2.0
base_model: HuggingFaceM4/idefics2-8b
tags:
- generated_from_trainer
model-index:
- name: 20240628-kibbe-training
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dubs/Kibbe-Training/runs/hqwk91zk)
# 20240628-kibbe-training
This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3663
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4649 | 0.5002 | 1032 | 0.4127 |
| 0.4276 | 1.0005 | 2064 | 0.3739 |
| 0.427 | 1.5007 | 3096 | 0.3663 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
ztchir/Reinforce-cartpole-v0 | ztchir | 2024-06-28T18:04:23Z | 0 | 0 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
]
| reinforcement-learning | 2024-06-28T18:04:14Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-cartpole-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
|
fsghs/Llama-2-7b-chat-finetune | fsghs | 2024-06-28T18:05:13Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:05:12Z | Entry not found |
Priyank-250/mistral-7b-bnb-4bit-freshworks-docss | Priyank-250 | 2024-06-28T18:05:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T18:05:27Z | ---
base_model: unsloth/mistral-7b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** Priyank-250
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
Priyank-250/mistral-7b-bnb-4bit-freshworks-docs | Priyank-250 | 2024-06-28T18:05:35Z | 0 | 0 | transformers | [
"transformers",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T18:05:34Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
UCringeRemade/LobotomyBunny | UCringeRemade | 2024-06-28T18:10:02Z | 0 | 0 | null | [
"license:openrail",
"region:us"
]
| null | 2024-06-28T18:09:07Z | ---
license: openrail
---
|
RasecAlvarez/example_model | RasecAlvarez | 2024-06-28T18:44:03Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:13:00Z | # Example model
This is the boilerplate README
---
license: mit
---
|
mttgermano/rl_course_vizdoom_health_gathering_supreme | mttgermano | 2024-06-28T18:14:34Z | 0 | 0 | sample-factory | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
]
| reinforcement-learning | 2024-06-28T18:14:12Z | ---
library_name: sample-factory
tags:
- deep-reinforcement-learning
- reinforcement-learning
- sample-factory
model-index:
- name: APPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: doom_health_gathering_supreme
type: doom_health_gathering_supreme
metrics:
- type: mean_reward
value: 12.99 +/- 5.92
name: mean_reward
verified: false
---
A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sample-Factory, download the model with:
```
python -m sample_factory.huggingface.load_from_hub -r mttgermano/rl_course_vizdoom_health_gathering_supreme
```
## Using the model
To run the model after download, use the `enjoy` script corresponding to this environment:
```
python -m .usr.local.lib.python3.10.dist-packages.colab_kernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme
```
You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag.
See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
## Training with this model
To continue training with this model, use the `train` script corresponding to this environment:
```
python -m .usr.local.lib.python3.10.dist-packages.colab_kernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000
```
Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
|
raprotv/Renata | raprotv | 2024-06-28T18:17:31Z | 0 | 0 | null | [
"license:afl-3.0",
"region:us"
]
| null | 2024-06-28T18:16:45Z | ---
license: afl-3.0
---
|
hemprakash/assignment2_model | hemprakash | 2024-06-28T18:17:40Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:17:39Z | Entry not found |
FevenTad/v1_0.15_Base | FevenTad | 2024-06-28T20:10:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T18:19:49Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
gaelafoxuk/ModelsPonyXL2 | gaelafoxuk | 2024-06-28T19:35:25Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:21:04Z | Entry not found |
EmoHugAI/distilbert-base-uncased-finetuned-imdb | EmoHugAI | 2024-06-28T18:21:30Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:21:30Z | Entry not found |
NAYEONCEot9cover/NAYEON | NAYEONCEot9cover | 2024-06-28T18:34:07Z | 0 | 0 | null | [
"license:openrail",
"region:us"
]
| null | 2024-06-28T18:31:38Z | ---
license: openrail
---
|
Lianhao/mit-b0-scene-parse-150-lora | Lianhao | 2024-06-28T19:04:28Z | 0 | 0 | null | [
"safetensors",
"region:us"
]
| null | 2024-06-28T18:34:47Z | Entry not found |
impossibleexchange/naschain | impossibleexchange | 2024-06-30T22:17:20Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:35:00Z | Entry not found |
Nex432/SonicAD100epoch | Nex432 | 2024-06-28T18:35:20Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:35:14Z | Entry not found |
Nutanix/Mistral-7B-Instruct-v0.3_KTO_lora_kto-mix-14k | Nutanix | 2024-06-28T20:22:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T18:41:39Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
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## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
therice2024/naschain | therice2024 | 2024-06-29T03:57:43Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:42:00Z | Entry not found |
calisoul/carin | calisoul | 2024-06-28T18:43:49Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:42:41Z | Entry not found |
calisoul/karol | calisoul | 2024-06-28T18:44:47Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:44:07Z | Entry not found |
Blue0666/Neos | Blue0666 | 2024-06-28T18:44:52Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:coversia21/RVC_Canserbero",
"region:us"
]
| text-to-image | 2024-06-28T18:44:52Z | ---
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/IMG_20240628_214434.jpg
base_model: coversia21/RVC_Canserbero
instance_prompt: null
---
# Neos
<Gallery />
## Download model
[Download](/Blue0666/Neos/tree/main) them in the Files & versions tab.
|
cumdom1/model_list | cumdom1 | 2024-06-29T17:55:03Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:48:11Z | Entry not found |
hungkvbn/naschain | hungkvbn | 2024-06-28T18:48:31Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T18:48:28Z | Entry not found |
Wassam123456/IMRAN_KHAN_1 | Wassam123456 | 2024-06-28T18:49:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T18:49:23Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses
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### Direct Use
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[More Information Needed]
### Downstream Use [optional]
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[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
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[More Information Needed]
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#### Preprocessing [optional]
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#### Speeds, Sizes, Times [optional]
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## Evaluation
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### Testing Data, Factors & Metrics
#### Testing Data
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[More Information Needed]
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#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
## Glossary [optional]
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[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
aileenchen/gpt2-wikitext2 | aileenchen | 2024-06-30T05:44:10Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
]
| text-generation | 2024-06-28T18:50:22Z | Entry not found |
LunLunVX/Meggy | LunLunVX | 2024-06-29T18:21:02Z | 0 | 0 | null | [
"license:other",
"region:us"
]
| null | 2024-06-28T19:02:01Z | ---
license: other
license_name: .pth
license_link: https://drive.google.com/file/d/1pNWBpkxbezeVqfnAGNgOUkNB1H-qV7AD/view
---
|
VaishVV/TourismLLMv1 | VaishVV | 2024-06-28T19:03:42Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T19:03:13Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
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[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
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[More Information Needed]
#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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Abhay06102003/Llama-3-FinanceAgent | Abhay06102003 | 2024-06-28T19:06:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-instruct-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T19:05:35Z | ---
base_model: unsloth/llama-3-8b-instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** Abhay06102003
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
abigail8n21/q-learning | abigail8n21 | 2024-06-28T19:15:36Z | 0 | 0 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
]
| reinforcement-learning | 2024-06-28T19:15:34Z | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-learning
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="abigail8n21/q-learning", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
tinylobsta/skyler-test-model | tinylobsta | 2024-06-28T19:16:06Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:16:06Z | Entry not found |
zeusnever/mi-demo | zeusnever | 2024-06-28T19:16:20Z | 0 | 0 | null | [
"license:mit",
"region:us"
]
| null | 2024-06-28T19:16:20Z | ---
license: mit
---
|
abigail8n21/q-learning-taxi3 | abigail8n21 | 2024-06-28T19:17:53Z | 0 | 0 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
]
| reinforcement-learning | 2024-06-28T19:17:51Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-learning-taxi3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.52 +/- 2.73
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="abigail8n21/q-learning-taxi3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
paulaolmedo/dqn-SpaceInvadersNoFrameskip-v4 | paulaolmedo | 2024-06-28T19:18:41Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:18:41Z | Entry not found |
Hivra/openai-medium.gguf | Hivra | 2024-06-28T19:21:36Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:21:36Z | Entry not found |
RimZrelli/CTL_Mistral_Instruct_12Fold_Param | RimZrelli | 2024-06-28T19:22:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T19:22:01Z | ---
base_model: unsloth/mistral-7b-instruct-v0.3-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** RimZrelli
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.3-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
IndianChessMans/lora_model | IndianChessMans | 2024-06-28T19:22:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-2-7b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T19:22:39Z | ---
base_model: unsloth/llama-2-7b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** IndianChessMans
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-2-7b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
ILKT/2024-06-24_00-11-56_epoch_8 | ILKT | 2024-06-28T19:25:05Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:25:05Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_9 | ILKT | 2024-06-28T19:25:23Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:25:22Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_10 | ILKT | 2024-06-28T19:25:39Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:25:39Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_11 | ILKT | 2024-06-28T19:25:57Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:25:56Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_12 | ILKT | 2024-06-28T19:26:14Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:26:13Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_13 | ILKT | 2024-06-28T19:26:31Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:26:30Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_14 | ILKT | 2024-06-28T19:26:48Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:26:48Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_15 | ILKT | 2024-06-28T19:27:30Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:27:29Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_16 | ILKT | 2024-06-28T19:27:51Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:27:50Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_17 | ILKT | 2024-06-28T19:28:09Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:28:09Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
Ahmad-11/crash_sev_expert200_ck420 | Ahmad-11 | 2024-06-28T19:28:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
]
| null | 2024-06-28T19:28:11Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
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## Training Details
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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<!-- Relevant interpretability work for the model goes here -->
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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## Model Card Contact
[More Information Needed] |
ILKT/2024-06-24_00-11-56_epoch_18 | ILKT | 2024-06-28T19:28:28Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:28:27Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_19 | ILKT | 2024-06-28T19:28:47Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:28:46Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_20 | ILKT | 2024-06-28T19:29:05Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:29:04Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
paulaolmedo/dqn-SpaceInvadersNoFrameskip-v4_ | paulaolmedo | 2024-06-28T19:29:13Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:29:13Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_21 | ILKT | 2024-06-28T19:29:22Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:29:22Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_22 | ILKT | 2024-06-28T19:29:40Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:29:39Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_23 | ILKT | 2024-06-28T19:29:58Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:29:57Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
marvinho-tn/aurora | marvinho-tn | 2024-06-28T19:30:09Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:30:09Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_24 | ILKT | 2024-06-28T19:30:16Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:30:15Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_25 | ILKT | 2024-06-28T19:30:34Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:30:33Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_26 | ILKT | 2024-06-28T19:30:51Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:30:51Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_27 | ILKT | 2024-06-28T19:31:09Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:31:08Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_28 | ILKT | 2024-06-28T19:31:27Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:31:26Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_29 | ILKT | 2024-06-28T19:31:45Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:31:44Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_30 | ILKT | 2024-06-28T19:32:03Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:32:02Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
guilhermebastos96/whisper-small-hi | guilhermebastos96 | 2024-06-28T19:32:13Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:32:13Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_31 | ILKT | 2024-06-28T19:32:20Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:32:20Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_32 | ILKT | 2024-06-28T19:32:38Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:32:37Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_33 | ILKT | 2024-06-28T19:32:58Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:32:56Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_34 | ILKT | 2024-06-28T19:33:18Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:33:17Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
guilhermebastos96/whisper-large-v3-finetuning | guilhermebastos96 | 2024-06-30T03:31:46Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2024-06-28T19:33:31Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_35 | ILKT | 2024-06-28T19:33:36Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:33:35Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_36 | ILKT | 2024-06-28T19:33:54Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:33:53Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_38 | ILKT | 2024-06-28T19:34:30Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:34:29Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_39 | ILKT | 2024-06-28T19:34:48Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:34:47Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_40 | ILKT | 2024-06-28T19:35:05Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:35:05Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_41 | ILKT | 2024-06-28T19:35:23Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:35:23Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_42 | ILKT | 2024-06-28T19:35:41Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:35:40Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_43 | ILKT | 2024-06-28T19:35:59Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:35:58Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_44 | ILKT | 2024-06-28T19:36:17Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:36:16Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
gaelafoxuk/ModelsXL2 | gaelafoxuk | 2024-06-28T19:44:28Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:36:20Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_45 | ILKT | 2024-06-28T19:36:35Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:36:34Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_46 | ILKT | 2024-06-28T19:36:53Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:36:52Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_47 | ILKT | 2024-06-28T19:37:11Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:37:10Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_48 | ILKT | 2024-06-28T19:37:29Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:37:28Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_49 | ILKT | 2024-06-28T19:37:46Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:37:45Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_50 | ILKT | 2024-06-28T19:38:04Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:38:03Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_51 | ILKT | 2024-06-28T19:38:22Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:38:21Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_52 | ILKT | 2024-06-28T19:38:40Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:38:39Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_53 | ILKT | 2024-06-28T19:38:57Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:38:56Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_54 | ILKT | 2024-06-28T19:39:15Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:39:14Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_55 | ILKT | 2024-06-28T19:39:33Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:39:32Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
Elahe96/dqn-SpaceInvadersNoFrameskip-1-v4 | Elahe96 | 2024-06-28T19:39:49Z | 0 | 0 | null | [
"region:us"
]
| null | 2024-06-28T19:39:49Z | Entry not found |
ILKT/2024-06-24_00-11-56_epoch_56 | ILKT | 2024-06-28T19:39:51Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:39:50Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_57 | ILKT | 2024-06-28T19:40:09Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:40:08Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_58 | ILKT | 2024-06-28T19:40:26Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:40:26Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_59 | ILKT | 2024-06-28T19:40:44Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:40:43Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_60 | ILKT | 2024-06-28T19:41:02Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:41:01Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_61 | ILKT | 2024-06-28T19:41:20Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:41:19Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
ILKT/2024-06-24_00-11-56_epoch_62 | ILKT | 2024-06-28T19:41:37Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"sentence-similarity",
"mteb",
"feature-extraction",
"en",
"pl",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| sentence-similarity | 2024-06-28T19:41:37Z | ---
language:
- en
- pl
model-index:
- name: PLACEHOLDER
results: []
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- mteb
- feature-extraction
---
|
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