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barca-boy
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primate_autotrain_sample

Text Generation
Transformers
Safetensors
llama
Trained with AutoTrain
conversational
text-generation-inference
Model card Files
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  1. README.md +40 -0
  2. checkpoint-880/README.md +202 -0
  3. checkpoint-880/adapter_config.json +28 -0
  4. checkpoint-880/adapter_model.safetensors +3 -0
  5. checkpoint-880/optimizer.pt +3 -0
  6. checkpoint-880/rng_state.pth +3 -0
  7. checkpoint-880/scheduler.pt +3 -0
  8. checkpoint-880/special_tokens_map.json +24 -0
  9. checkpoint-880/tokenizer.json +0 -0
  10. checkpoint-880/tokenizer.model +3 -0
  11. checkpoint-880/tokenizer_config.json +42 -0
  12. checkpoint-880/trainer_state.json +637 -0
  13. checkpoint-880/training_args.bin +3 -0
  14. config.json +28 -0
  15. generation_config.json +10 -0
  16. model-00001-of-00003.safetensors +3 -0
  17. model-00002-of-00003.safetensors +3 -0
  18. model-00003-of-00003.safetensors +3 -0
  19. model.safetensors.index.json +298 -0
  20. special_tokens_map.json +30 -0
  21. tokenizer.json +0 -0
  22. tokenizer.model +3 -0
  23. tokenizer_config.json +42 -0
  24. training_args.bin +3 -0
  25. training_params.json +47 -0
README.md ADDED
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+ ---
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+ tags:
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+ - autotrain
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+ - text-generation
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+ widget:
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+ - text: "I love AutoTrain because "
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+ license: other
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+ ---
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+
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+ # Model Trained Using AutoTrain
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+
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+ This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
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+
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+ # Usage
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+
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+ ```python
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+
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_path = "PATH_TO_THIS_REPO"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_path)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_path,
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+ device_map="auto",
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+ torch_dtype='auto'
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+ ).eval()
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+
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+ # Prompt content: "hi"
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+ messages = [
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+ {"role": "user", "content": "hi"}
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+ ]
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+
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+ input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
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+ output_ids = model.generate(input_ids.to('cuda'))
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+ response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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+
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+ # Model response: "Hello! How can I assist you today?"
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+ print(response)
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+ ```
checkpoint-880/README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: meta-llama/Llama-2-7b-hf
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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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+
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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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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- 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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+
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+ #### Summary
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+
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+
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+
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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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+
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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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+
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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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+
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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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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+
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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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+
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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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+
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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]
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+ ### Framework versions
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+
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+ - PEFT 0.9.0
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