- .DS_Store +0 -0
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/README.md +0 -63
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/adapter_config.json +0 -38
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/adapter_model.safetensors +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/README.md +0 -202
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/adapter_config.json +0 -38
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/adapter_model.safetensors +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/optimizer.pt +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/rng_state.pth +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/scheduler.pt +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/trainer_state.json +0 -255
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/training_args.bin +0 -3
- checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/training_args.bin +0 -3
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---
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library_name: peft
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tags:
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base_model: /workspace/ROCO2nd_RSV_llava-v1.6-mistral_PMC
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model-index:
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- name: LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1624
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.2313 | 0.6504 | 100 | 0.1906 |
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| 0.1266 | 1.3008 | 200 | 0.1662 |
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| 0.1422 | 1.9512 | 300 | 0.1624 |
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### Framework versions
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- PEFT 0.10.1.dev0
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- Transformers 4.40.1
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- Pytorch 2.1.1+cu121
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- Datasets 2.19.0
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checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": {
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"base_model_class": "LlavaMistralForCausalLM",
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"parent_library": "llava.model.language_model.llava_mistral"
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},
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"base_model_name_or_path": "/workspace/ROCO2nd_RSV_llava-v1.6-mistral_PMC",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"mm_projector"
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],
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"q_proj",
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"up_proj",
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],
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"task_type": null,
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"use_dora": false,
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"use_rslora": false
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}
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checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a52b158e0bf56fe7d229df377cebe6bcebdc74d77efae5a011efb65184a5a97
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size 122253960
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checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/README.md
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---
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library_name: peft
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base_model: /workspace/ROCO2nd_RSV_llava-v1.6-mistral_PMC
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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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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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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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 -->
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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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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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#### Software
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[More Information Needed]
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## Citation [optional]
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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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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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checkpoints/LS_ROCO2nd_RSV_llava-v1.6-mistral_PMC/checkpoint-300/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": {
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"base_model_class": "LlavaMistralForCausalLM",
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