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  1. .gitattributes +3 -0
  2. gemma-2b-distilled/README.md +75 -0
  3. gemma-2b-distilled/checkpoint-150/README.md +209 -0
  4. gemma-2b-distilled/checkpoint-150/adapter_config.json +46 -0
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.gitattributes CHANGED
@@ -49,3 +49,6 @@ gemma-2b-dpo/checkpoint-450/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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  gemma-2b-dpo/checkpoint-50/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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  gemma-2b-dpo/checkpoint-500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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  gemma-2b-dpo/checkpoint-540/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  gemma-2b-dpo/checkpoint-540/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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gemma-2b-distilled/README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/gemma-2-2b-it
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+ tags:
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+ - medical
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+ - clinical-notes
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+ - patient-communication
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+ - lora
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+ - peft
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+ - medgemma
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+ language:
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+ - en
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+ library_name: peft
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+ ---
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+
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+ # gemma-2b-distilled
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+
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+ Gemma-2B fine-tuned via knowledge distillation from Gemma-9B-DPO for clinical note simplification
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+
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+ ## Model Details
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+
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+ - **Base model**: [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it)
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+ - **Training method**: SFT distillation from 9B-DPO teacher (600 samples)
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+ - **Task**: Clinical note simplification for patient communication
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+ - **License**: Apache 2.0
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+
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+ ## Performance
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+
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+ | Metric | Score |
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+ |--------|-------|
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+ | Overall | 70% |
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+ | Accuracy | 73% |
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+ | Patient-Centered | 76% |
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+
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+ Evaluated by MedGemma-27B (`google/medgemma-27b-text-it`) on 50 held-out clinical notes.
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+
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+ ## Usage
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+
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+ ```python
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+ from peft import PeftModel
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ # Load base model
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+ base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it")
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+ tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b-it")
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+
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+ # Load LoRA adapter
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+ model = PeftModel.from_pretrained(base_model, "dejori/note-explain-gemma-2b-distilled")
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+
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+ # Generate
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+ prompt = "Simplify this clinical note for a patient:\n\n[your clinical note]\n\nSimplified version:"
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+ inputs = tokenizer(prompt, return_tensors="pt")
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+ outputs = model.generate(**inputs, max_new_tokens=512)
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+ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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+ ```
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+
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+ ## Training Data
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+
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+ Trained on [dejori/note-explain-clinical](https://huggingface.co/datasets/dejori/note-explain-clinical) dataset.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @misc{noteexplain2026,
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+ title={NoteExplain: Privacy-First Clinical Note Simplification},
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+ author={Dejori, Mathaeus},
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+ year={2026},
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+ publisher={HuggingFace}
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+ }
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+ ```
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+
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+ ## Related
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+
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+ - **Dataset**: [dejori/note-explain-clinical](https://huggingface.co/datasets/dejori/note-explain-clinical)
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+ - **Project**: [MedGemma Impact Challenge Submission](https://github.com/dejori/note-explain)
gemma-2b-distilled/checkpoint-150/README.md ADDED
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+ ---
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+ base_model: google/gemma-2-2b-it
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+ library_name: peft
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+ pipeline_tag: text-generation
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+ tags:
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+ - base_model:adapter:google/gemma-2-2b-it
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+ - lora
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+ - sft
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+ - transformers
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+ - trl
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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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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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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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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+
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+ ## Uses
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+
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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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+
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+ ### Direct Use
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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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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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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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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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
122
+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
126
+ [More Information Needed]
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+
128
+ #### Metrics
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+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
138
+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
144
+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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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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+
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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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+
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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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+
160
+ ## Technical Specifications [optional]
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+
162
+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
170
+ #### Hardware
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+
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+ [More Information Needed]
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+
174
+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
179
+
180
+ <!-- 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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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
207
+ ### Framework versions
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+
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+ - PEFT 0.18.1
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+ ---
2
+ base_model: google/gemma-2-2b-it
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+ library_name: peft
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+ pipeline_tag: text-generation
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+ tags:
6
+ - base_model:adapter:google/gemma-2-2b-it
7
+ - lora
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+ - sft
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+ - transformers
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+ ---
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+ # Model Card for Model ID
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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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+ ## Training Details
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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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+ ### Framework versions
208
+
209
+ - PEFT 0.18.1
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+ ---
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+ base_model: google/gemma-2-2b-it
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+ library_name: peft
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+ pipeline_tag: text-generation
5
+ tags:
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+ - base_model:adapter:google/gemma-2-2b-it
7
+ - lora
8
+ - sft
9
+ - transformers
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+ - trl
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+
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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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+ - **License:** [More Information Needed]
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+
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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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+
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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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+
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+ ## Bias, Risks, and Limitations
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+
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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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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ ### Training Procedure
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+
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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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+
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+ #### Preprocessing [optional]
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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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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+
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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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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+ [More Information Needed]
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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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+ ### Results
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+ #### Summary
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+ ## Model Examination [optional]
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+
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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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+
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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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+
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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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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+ [More Information Needed]
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+ #### Hardware
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+ [More Information Needed]
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+
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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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+ ## 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]
207
+ ### Framework versions
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+
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+ - PEFT 0.18.1
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