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|---|---|---|---|---|---|---|---|---|---|
mclemcrew/mert-330-audio-effect-classification
|
mclemcrew
| 2024-06-26T21:39:31Z | 0 | 0 | null |
[
"safetensors",
"region:us"
] | null | 2024-06-26T21:14:26Z |
Entry not found
|
lit9003code/melotts235
|
lit9003code
| 2024-06-26T21:16:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:15:53Z |
Entry not found
|
habulaj/445631414155
|
habulaj
| 2024-06-26T21:16:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:16:21Z |
Entry not found
|
lit9003code/melotts236
|
lit9003code
| 2024-06-26T21:17:42Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:17:26Z |
Entry not found
|
lit9003code/melotts237
|
lit9003code
| 2024-06-26T21:20:05Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:19:01Z |
Entry not found
|
lit9003code/melotts238
|
lit9003code
| 2024-06-26T21:21:34Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:21:14Z |
Entry not found
|
lit9003code/melotts239
|
lit9003code
| 2024-06-26T21:23:07Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:22:49Z |
Entry not found
|
todor02/llamatest
|
todor02
| 2024-06-26T21:23:28Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:23:28Z |
Entry not found
|
shayan000/remla24-team10-phishing-detector
|
shayan000
| 2024-06-26T21:24:08Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2024-06-26T21:24:08Z |
---
license: mit
---
|
lit9003code/melotts240
|
lit9003code
| 2024-06-26T21:24:30Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:24:14Z |
Entry not found
|
habulaj/4238735032
|
habulaj
| 2024-06-26T21:24:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:24:45Z |
Entry not found
|
lit9003code/melotts241
|
lit9003code
| 2024-06-26T21:25:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:25:37Z |
Entry not found
|
habulaj/12329798054
|
habulaj
| 2024-06-26T21:26:27Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:26:20Z |
Entry not found
|
jayoohwang/alpham-ckpt
|
jayoohwang
| 2024-06-26T21:30:28Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2024-06-26T21:26:57Z |
Entry not found
|
lit9003code/melotts242
|
lit9003code
| 2024-06-26T21:27:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:27:00Z |
Entry not found
|
ej-codes/Orpo-Llama-8B-Future2Present
|
ej-codes
| 2024-06-26T21:27:15Z | 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 | 2024-06-26T21:27:05Z |
---
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:** ej-codes
- **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)
|
habulaj/1660216368
|
habulaj
| 2024-06-26T21:27:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:27:55Z |
Entry not found
|
lit9003code/melotts243
|
lit9003code
| 2024-06-26T21:29:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:28:37Z |
Entry not found
|
habulaj/48445758
|
habulaj
| 2024-06-26T21:29:52Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:29:36Z |
Entry not found
|
lit9003code/melotts244
|
lit9003code
| 2024-06-26T21:32:19Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:31:05Z |
Entry not found
|
alex2020xx/selfie
|
alex2020xx
| 2024-06-26T21:31:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:31:08Z |
Entry not found
|
habulaj/1998219691
|
habulaj
| 2024-06-26T21:33:36Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:33:21Z |
Entry not found
|
lit9003code/melotts245
|
lit9003code
| 2024-06-26T21:33:41Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:33:25Z |
Entry not found
|
habulaj/11842792996
|
habulaj
| 2024-06-26T21:34:16Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:34:06Z |
Entry not found
|
aben118/tiny-common-voice-finetuning-server-10k-2-enc-hub
|
aben118
| 2024-06-26T21:34:15Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T21:34:14Z |
---
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]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
|
Litzy619/MIS0626T2F200200
|
Litzy619
| 2024-06-27T00:12:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:34:59Z |
Entry not found
|
lit9003code/melotts246
|
lit9003code
| 2024-06-26T21:36:09Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:35:01Z |
Entry not found
|
serifagir/cup-or-mug
|
serifagir
| 2024-06-26T21:36:19Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2024-06-26T21:36:18Z |
---
license: apache-2.0
---
|
lit9003code/melotts247
|
lit9003code
| 2024-06-26T21:38:29Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:37:18Z |
Entry not found
|
abhikrnigam/LlamaFinetuned_alpaca
|
abhikrnigam
| 2024-06-26T21:40:44Z | 0 | 0 | null |
[
"safetensors",
"en",
"dataset:yahma/alpaca-cleaned",
"license:apache-2.0",
"region:us"
] | null | 2024-06-26T21:37:55Z |
---
license: apache-2.0
datasets:
- yahma/alpaca-cleaned
language:
- en
---
|
lit9003code/melotts248
|
lit9003code
| 2024-06-26T21:40:12Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:39:56Z |
Entry not found
|
dixitrivedi/cft_mistral_v3__hindi
|
dixitrivedi
| 2024-06-26T21:41:22Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-v0.3-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T21:40:14Z |
---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** dixitrivedi
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-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)
|
TioPanda/pandev-complete-instruction
|
TioPanda
| 2024-06-26T21:41:15Z | 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 | 2024-06-26T21:40:49Z |
---
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:** TioPanda
- **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)
|
spjabech/Twitch_Highlighter_audio_llama
|
spjabech
| 2024-06-26T21:41:28Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:41:27Z |
Entry not found
|
Azaz666/gpt2-finetuned-CEP
|
Azaz666
| 2024-06-26T21:41:52Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:41:52Z |
Entry not found
|
spjabech/Twitch_Highlighter_audio_ohnetimestamps_phi
|
spjabech
| 2024-06-26T21:42:02Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:42:02Z |
Entry not found
|
pranay-ar/unimatch
|
pranay-ar
| 2024-06-26T21:46:02Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2024-06-26T21:42:57Z |
---
license: mit
---
|
lmorlok/llmSeqDes
|
lmorlok
| 2024-06-26T21:44:27Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:44:27Z |
Entry not found
|
spjabech/Twitch_Highlighter_audio_ohnetimestamps_llama
|
spjabech
| 2024-06-26T21:45:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:45:45Z |
Entry not found
|
Grayx/john_paul_van_damme_41
|
Grayx
| 2024-06-26T21:51:14Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:50:59Z |
Entry not found
|
Litzy619/MIS0626T1F200200
|
Litzy619
| 2024-06-27T01:04:22Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:51:07Z |
Entry not found
|
naimul011/Ag-Senti-llama3
|
naimul011
| 2024-06-26T21:51:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T21:51:54Z |
Entry not found
|
spjabech/Twitch_Highlighter_chat_ohnetimestamps_phi
|
spjabech
| 2024-06-26T22:00:08Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:00:08Z |
Entry not found
|
spjabech/Twitch_Highlighter_chat_ohnetimestamps_llama
|
spjabech
| 2024-06-26T22:00:18Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:00:18Z |
Entry not found
|
qsdreams/kandi
|
qsdreams
| 2024-06-26T22:01:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:01:45Z |
Entry not found
|
spjabech/Twitch_Highlighter_chat_phi
|
spjabech
| 2024-06-26T22:02:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:02:20Z |
Entry not found
|
habulaj/204020177213
|
habulaj
| 2024-06-26T22:02:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:02:21Z |
Entry not found
|
spjabech/Twitch_Highlighter_chat_llama
|
spjabech
| 2024-06-26T22:02:32Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:02:32Z |
Entry not found
|
spjabech/Twitch_Highlighter_combined_ohnetimestamps_phi
|
spjabech
| 2024-06-26T22:02:48Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:02:48Z |
Entry not found
|
spjabech/Twitch_Highlighter_combined_phi
|
spjabech
| 2024-06-26T22:03:34Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:03:34Z |
Entry not found
|
spjabech/Twitch_Highlighter_combined_llama
|
spjabech
| 2024-06-26T22:03:42Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:03:42Z |
Entry not found
|
TioPanda/pandev-complete-gemma
|
TioPanda
| 2024-06-26T22:05:33Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"gemma",
"trl",
"en",
"base_model:unsloth/gemma-7b-it-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:05:13Z |
---
base_model: unsloth/gemma-7b-it-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
---
# Uploaded model
- **Developed by:** TioPanda
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-7b-it-bnb-4bit
This gemma 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)
|
Ahmedmagdy9581/Ahmed
|
Ahmedmagdy9581
| 2024-06-26T22:07:32Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2024-06-26T22:07:32Z |
---
license: apache-2.0
---
|
habulaj/5265271874
|
habulaj
| 2024-06-26T22:13:16Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:13:10Z |
Entry not found
|
bug7/base_1139
|
bug7
| 2024-06-26T22:13:31Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:13:23Z |
---
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]
<!-- 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]
|
habulaj/7875472818
|
habulaj
| 2024-06-26T22:14:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:14:19Z |
Entry not found
|
LinxuanPastel/tuffy
|
LinxuanPastel
| 2024-06-26T22:51:47Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:17:26Z |
Entry not found
|
wassemgtk/mergekit-passthrough-oomzneg
|
wassemgtk
| 2024-06-26T22:18:31Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:18:31Z |
Entry not found
|
saifhmb/fraud-detection-model
|
saifhmb
| 2024-06-29T16:19:05Z | 0 | 0 |
sklearn
|
[
"sklearn",
"skops",
"tabular-classification",
"finance",
"region:us"
] |
tabular-classification
| 2024-06-26T22:20:17Z |
---
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
- finance
model_format: pickle
model_file: skops-ise057qg.pkl
widget:
- structuredData:
Bene_Country:
- COMOROS
- CANADA
- MOROCCO
Sender_Country:
- SRI-LANKA
- USA
- USA
Transaction_Type:
- MOVE-FUNDS
- PAY-CHECK
- MAKE-PAYMENT
USD_amount:
- 598.31
- 398.72
- 87.03
---
# Model description
This is a Gaussian Naive Bayes model trained on a synthetic dataset, containining a large variety of transaction types representing normal activities as well as
abnormal/fraudulent activities generated by J.P. Morgan AI Research. The model predicts whether a transaction is normal or fraudulent.
## Intended uses & limitations
For educational purposes
## Training Procedure
The data preprocessing steps applied include the following:
- Dropping high cardinality features. This includes Transaction ID, Sender ID, Sender Account, Beneficiary ID, Beneficiary Account, Sender Sector
- Dropping no variance features. This includes Sender LOB
- Dropping Time and date feature since the model is not time-series based
- Transforming and Encoding categorical features namely: Sender Country, Beneficiary Country, Transaction Type, and the target variable, Label
- Applying feature scaling on all features
- Splitting the dataset into training/test set using 85/15 split ratio
- Handling imbalanced dataset using imblearn framework and applying RandomUnderSampler method to eliminate noise which led to a 2.5% improvement in accuracy
### Hyperparameters
<details>
<summary> Click to expand </summary>
| Hyperparameter | Value |
|----------------------------------------------|---------------------------------------------------------------------------|
| memory | |
| steps | [('preprocessorAll', ColumnTransformer(remainder='passthrough',<br /> transformers=[('cat',<br /> Pipeline(steps=[('onehot',<br /> OneHotEncoder(handle_unknown='ignore',<br /> sparse_output=False))]),<br /> ['Sender_Country', 'Bene_Country',<br /> 'Transaction_Type']),<br /> ('num',<br /> Pipeline(steps=[('scale', StandardScaler())]),<br /> Index(['USD_amount'], dtype='object'))])), ('classifier', GaussianNB())] |
| verbose | False |
| preprocessorAll | ColumnTransformer(remainder='passthrough',<br /> transformers=[('cat',<br /> Pipeline(steps=[('onehot',<br /> OneHotEncoder(handle_unknown='ignore',<br /> sparse_output=False))]),<br /> ['Sender_Country', 'Bene_Country',<br /> 'Transaction_Type']),<br /> ('num',<br /> Pipeline(steps=[('scale', StandardScaler())]),<br /> Index(['USD_amount'], dtype='object'))]) |
| classifier | GaussianNB() |
| preprocessorAll__n_jobs | |
| preprocessorAll__remainder | passthrough |
| preprocessorAll__sparse_threshold | 0.3 |
| preprocessorAll__transformer_weights | |
| preprocessorAll__transformers | [('cat', Pipeline(steps=[('onehot',<br /> OneHotEncoder(handle_unknown='ignore', sparse_output=False))]), ['Sender_Country', 'Bene_Country', 'Transaction_Type']), ('num', Pipeline(steps=[('scale', StandardScaler())]), Index(['USD_amount'], dtype='object'))] |
| preprocessorAll__verbose | False |
| preprocessorAll__verbose_feature_names_out | True |
| preprocessorAll__cat | Pipeline(steps=[('onehot',<br /> OneHotEncoder(handle_unknown='ignore', sparse_output=False))]) |
| preprocessorAll__num | Pipeline(steps=[('scale', StandardScaler())]) |
| preprocessorAll__cat__memory | |
| preprocessorAll__cat__steps | [('onehot', OneHotEncoder(handle_unknown='ignore', sparse_output=False))] |
| preprocessorAll__cat__verbose | False |
| preprocessorAll__cat__onehot | OneHotEncoder(handle_unknown='ignore', sparse_output=False) |
| preprocessorAll__cat__onehot__categories | auto |
| preprocessorAll__cat__onehot__drop | |
| preprocessorAll__cat__onehot__dtype | <class 'numpy.float64'> |
| preprocessorAll__cat__onehot__handle_unknown | ignore |
| preprocessorAll__cat__onehot__max_categories | |
| preprocessorAll__cat__onehot__min_frequency | |
| preprocessorAll__cat__onehot__sparse | deprecated |
| preprocessorAll__cat__onehot__sparse_output | False |
| preprocessorAll__num__memory | |
| preprocessorAll__num__steps | [('scale', StandardScaler())] |
| preprocessorAll__num__verbose | False |
| preprocessorAll__num__scale | StandardScaler() |
| preprocessorAll__num__scale__copy | True |
| preprocessorAll__num__scale__with_mean | True |
| preprocessorAll__num__scale__with_std | True |
| classifier__priors | |
| classifier__var_smoothing | 1e-09 |
</details>
### Model Plot
<style>#sk-container-id-6 {color: black;background-color: white;}#sk-container-id-6 pre{padding: 0;}#sk-container-id-6 div.sk-toggleable {background-color: white;}#sk-container-id-6 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-6 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-6 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-6 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-6 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-6 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-6 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-6 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-6 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-6 div.sk-item {position: relative;z-index: 1;}#sk-container-id-6 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-6 div.sk-item::before, #sk-container-id-6 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-6 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-6 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-6 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-6 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-6 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-6 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-6 div.sk-label-container {text-align: center;}#sk-container-id-6 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-6 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-6" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('preprocessorAll',ColumnTransformer(remainder='passthrough',transformers=[('cat',Pipeline(steps=[('onehot',OneHotEncoder(handle_unknown='ignore',sparse_output=False))]),['Sender_Country','Bene_Country','Transaction_Type']),('num',Pipeline(steps=[('scale',StandardScaler())]),Index(['USD_amount'], dtype='object'))])),('classifier', GaussianNB())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-46" type="checkbox" ><label for="sk-estimator-id-46" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[('preprocessorAll',ColumnTransformer(remainder='passthrough',transformers=[('cat',Pipeline(steps=[('onehot',OneHotEncoder(handle_unknown='ignore',sparse_output=False))]),['Sender_Country','Bene_Country','Transaction_Type']),('num',Pipeline(steps=[('scale',StandardScaler())]),Index(['USD_amount'], dtype='object'))])),('classifier', GaussianNB())])</pre></div></div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-47" type="checkbox" ><label for="sk-estimator-id-47" class="sk-toggleable__label sk-toggleable__label-arrow">preprocessorAll: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(remainder='passthrough',transformers=[('cat',Pipeline(steps=[('onehot',OneHotEncoder(handle_unknown='ignore',sparse_output=False))]),['Sender_Country', 'Bene_Country','Transaction_Type']),('num',Pipeline(steps=[('scale', StandardScaler())]),Index(['USD_amount'], dtype='object'))])</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-48" type="checkbox" ><label for="sk-estimator-id-48" class="sk-toggleable__label sk-toggleable__label-arrow">cat</label><div class="sk-toggleable__content"><pre>['Sender_Country', 'Bene_Country', 'Transaction_Type']</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-49" type="checkbox" ><label for="sk-estimator-id-49" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder(handle_unknown='ignore', sparse_output=False)</pre></div></div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-50" type="checkbox" ><label for="sk-estimator-id-50" class="sk-toggleable__label sk-toggleable__label-arrow">num</label><div class="sk-toggleable__content"><pre>Index(['USD_amount'], dtype='object')</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-51" type="checkbox" ><label for="sk-estimator-id-51" class="sk-toggleable__label sk-toggleable__label-arrow">StandardScaler</label><div class="sk-toggleable__content"><pre>StandardScaler()</pre></div></div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-52" type="checkbox" ><label for="sk-estimator-id-52" class="sk-toggleable__label sk-toggleable__label-arrow">remainder</label><div class="sk-toggleable__content"><pre>[]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-53" type="checkbox" ><label for="sk-estimator-id-53" class="sk-toggleable__label sk-toggleable__label-arrow">passthrough</label><div class="sk-toggleable__content"><pre>passthrough</pre></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-54" type="checkbox" ><label for="sk-estimator-id-54" class="sk-toggleable__label sk-toggleable__label-arrow">GaussianNB</label><div class="sk-toggleable__content"><pre>GaussianNB()</pre></div></div></div></div></div></div></div>
## Evaluation Results
| Metric | Value |
|----------|----------|
| accuracy | 0.794582 |
### Confusion Matrix
# Model Card Authors
This model card is written by following authors: Seifullah Bello
|
jacobcd52/physics-papers
|
jacobcd52
| 2024-06-26T22:22:03Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:22:03Z |
Entry not found
|
wassemgtk/mergekit-passthrough-sfqpbok
|
wassemgtk
| 2024-06-26T22:27:27Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:27:27Z |
Entry not found
|
rg1683/hindi_wordpiece_tokenizer
|
rg1683
| 2024-06-27T17:37:09Z | 0 | 0 |
transformers
|
[
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:27:44Z |
---
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]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
|
habulaj/9381170820
|
habulaj
| 2024-06-26T22:31:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:31:55Z |
Entry not found
|
martinkozle/MKLLM-7B-Instruct-exl2
|
martinkozle
| 2024-06-27T00:57:40Z | 0 | 0 | null |
[
"axolotl",
"exl2",
"mk",
"en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | 2024-06-26T22:33:13Z |
---
license: cc-by-nc-sa-4.0
language:
- mk
- en
tags:
- axolotl
- exl2
---
# MKLLM-7B-Instruct-exl2
EXL2 quants of [trajkovnikola/MKLLM-7B-Instruct](https://huggingface.co/trajkovnikola/MKLLM-7B-Instruct)
<b>The "main" branch only contains the measurement.json (which can be used for further conversions), download one of the other branches for the model:</b>
[6.5 bits per weight with 6 lm_head bits](https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2/tree/6.5bpw-h6)
[5.0 bits per weight with 6 lm_head bits](https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2/tree/5.0bpw-h6)
[4.25 bits per weight with 6 lm_head bits](https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2/tree/4.25bpw-h6)
[3.5 bits per weight with 6 lm_head bits](https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2/tree/3.5bpw-h6)
[measurement.json](https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2/blob/main/measurement.json)
## Download instructions
With git:
```shell
git clone --single-branch --branch 5.0bpw-h6 https://huggingface.co/martinkozle/MKLLM-7B-Instruct-exl2 MKLLM-7B-Instruct-exl2-5.0bpw-h6
```
With huggingface hub:
To download a specific branch, use the `--revision` parameter.
```shell
huggingface-cli download martinkozle/MKLLM-7B-Instruct-exl2 --revision 5.0bpw-h6 --local-dir MKLLM-7B-Instruct-exl2-5.0bpw-h6 --local-dir-use-symlinks False
```
|
arve3210/lora_model
|
arve3210
| 2024-06-26T22:34:41Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:34:23Z |
---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** arve3210
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-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)
|
habulaj/4496038468
|
habulaj
| 2024-06-26T22:34:44Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:34:38Z |
Entry not found
|
habulaj/441632409862
|
habulaj
| 2024-06-26T22:36:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:36:14Z |
Entry not found
|
habulaj/212532189513
|
habulaj
| 2024-06-26T22:38:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:38:02Z |
Entry not found
|
wassemgtk/mergekit-passthrough-thwapmv
|
wassemgtk
| 2024-06-26T22:41:49Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:41:49Z |
Entry not found
|
bug7/base_120
|
bug7
| 2024-06-26T22:42:26Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:42:14Z |
---
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]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
|
habulaj/207827180626
|
habulaj
| 2024-06-26T22:45:12Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:45:07Z |
Entry not found
|
habulaj/10806682948
|
habulaj
| 2024-06-26T22:45:12Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:45:09Z |
Entry not found
|
Ramikan-BR/TiamaPY-LORA-v37
|
Ramikan-BR
| 2024-06-26T22:47:21Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/tinyllama-chat-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:46:41Z |
---
base_model: unsloth/tinyllama-chat-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** Ramikan-BR
- **License:** apache-2.0
- **Finetuned from model :** unsloth/tinyllama-chat-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)
|
alexzarate/gerard_pique
|
alexzarate
| 2024-06-26T23:16:33Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:50:03Z |
Entry not found
|
FevenTad/v1_0.65_1
|
FevenTad
| 2024-06-26T22:54:12Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-06-26T22:52:36Z |
---
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]
|
syamak6bits/esm2_t12_35M_UR50D-finetuned-localization
|
syamak6bits
| 2024-07-01T11:10:21Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"esm",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2024-06-26T22:53:27Z |
Entry not found
|
karim8/math
|
karim8
| 2024-06-26T22:57:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T22:57:25Z |
Entry not found
|
vinisebk/jo_sclub
|
vinisebk
| 2024-06-26T23:02:08Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2024-06-26T23:00:19Z |
---
license: openrail
---
|
welcometoea/r1l3ystar
|
welcometoea
| 2024-06-26T23:14:26Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:00:48Z |
Entry not found
|
habulaj/381076346766
|
habulaj
| 2024-06-26T23:01:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:01:08Z |
Entry not found
|
Jahzz/Image_Segmentation_v1
|
Jahzz
| 2024-06-26T23:07:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:06:33Z |
Entry not found
|
habulaj/270688240990
|
habulaj
| 2024-06-26T23:06:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:06:46Z |
Entry not found
|
lucassissy12/your-model-name
|
lucassissy12
| 2024-06-26T23:10:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:10:06Z |
Entry not found
|
lucassissy12/Aishah_Sofey
|
lucassissy12
| 2024-06-26T23:15:31Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:15:31Z |
Entry not found
|
habulaj/28600427253
|
habulaj
| 2024-06-26T23:18:43Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:18:31Z |
Entry not found
|
habulaj/7693772827
|
habulaj
| 2024-06-26T23:19:04Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:18:57Z |
Entry not found
|
kaengpil/nakyoung
|
kaengpil
| 2024-06-26T23:20:06Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2024-06-26T23:19:49Z |
---
license: openrail
---
|
habulaj/7899757293
|
habulaj
| 2024-06-26T23:22:08Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:22:06Z |
Entry not found
|
SilvioLima/absa_domain_restaurant
|
SilvioLima
| 2024-06-29T00:53:33Z | 0 | 0 | null |
[
"safetensors",
"region:us"
] | null | 2024-06-26T23:22:57Z |
### Domain
Laptop 81.612245
Restaurant 78.349398
book 61.833333
beauty 55.900000
electronics 52.562500
fashion 51.928571
home 50.923077
pet 46.000000
toy 39.714286
grocery 35.000000
### F1-score% mean = 73.2473
|
Rodolfo074/brad_simpson
|
Rodolfo074
| 2024-06-26T23:24:29Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:24:13Z |
Entry not found
|
habulaj/9911674609
|
habulaj
| 2024-06-26T23:25:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:25:56Z |
Entry not found
|
ChenmieNLP/zephyr-7b-dpo-full
|
ChenmieNLP
| 2024-06-26T23:26:00Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:25:59Z |
Entry not found
|
ErikGG64/Kurt_NEVERMIND_era_400E
|
ErikGG64
| 2024-06-26T23:34:33Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2024-06-26T23:27:17Z |
---
license: openrail
---
|
habulaj/429926425800
|
habulaj
| 2024-06-26T23:28:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:27:39Z |
Entry not found
|
habulaj/129031103898
|
habulaj
| 2024-06-26T23:31:01Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:30:53Z |
Entry not found
|
habulaj/448703417360
|
habulaj
| 2024-06-26T23:33:23Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:33:16Z |
Entry not found
|
henilp105/InjecAgent-llama-7b-optim-all-15
|
henilp105
| 2024-06-27T04:39:25Z | 0 | 0 | null |
[
"safetensors",
"region:us"
] | null | 2024-06-26T23:37:29Z |
Entry not found
|
habulaj/279026248536
|
habulaj
| 2024-06-26T23:39:08Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:38:56Z |
Entry not found
|
habulaj/282687251718
|
habulaj
| 2024-06-26T23:51:43Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:51:33Z |
Entry not found
|
jykim310/llava-1.5-7b-clip-base-q4f16_1-MLC
|
jykim310
| 2024-06-26T23:55:05Z | 0 | 0 | null |
[
"region:us"
] | null | 2024-06-26T23:52:56Z |
Entry not found
|
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