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  1. README.md +72 -0
  2. adapter_config.json +37 -0
  3. adapter_model.safetensors +3 -0
  4. checkpoint-400/README.md +202 -0
  5. checkpoint-400/adapter_config.json +37 -0
  6. checkpoint-400/adapter_model.safetensors +3 -0
  7. checkpoint-400/optimizer.pt +3 -0
  8. checkpoint-400/rng_state.pth +3 -0
  9. checkpoint-400/scheduler.pt +3 -0
  10. checkpoint-400/special_tokens_map.json +30 -0
  11. checkpoint-400/tokenizer.json +0 -0
  12. checkpoint-400/tokenizer.model +3 -0
  13. checkpoint-400/tokenizer_config.json +84 -0
  14. checkpoint-400/trainer_state.json +345 -0
  15. checkpoint-400/training_args.bin +3 -0
  16. checkpoint-500/README.md +202 -0
  17. checkpoint-500/adapter_config.json +37 -0
  18. checkpoint-500/adapter_model.safetensors +3 -0
  19. checkpoint-500/optimizer.pt +3 -0
  20. checkpoint-500/rng_state.pth +3 -0
  21. checkpoint-500/scheduler.pt +3 -0
  22. checkpoint-500/special_tokens_map.json +30 -0
  23. checkpoint-500/tokenizer.json +0 -0
  24. checkpoint-500/tokenizer.model +3 -0
  25. checkpoint-500/tokenizer_config.json +84 -0
  26. checkpoint-500/trainer_state.json +423 -0
  27. checkpoint-500/training_args.bin +3 -0
  28. checkpoint-597/README.md +202 -0
  29. checkpoint-597/adapter_config.json +37 -0
  30. checkpoint-597/adapter_model.safetensors +3 -0
  31. checkpoint-597/optimizer.pt +3 -0
  32. checkpoint-597/rng_state.pth +3 -0
  33. checkpoint-597/scheduler.pt +3 -0
  34. checkpoint-597/special_tokens_map.json +30 -0
  35. checkpoint-597/tokenizer.json +0 -0
  36. checkpoint-597/tokenizer.model +3 -0
  37. checkpoint-597/tokenizer_config.json +84 -0
  38. checkpoint-597/trainer_state.json +486 -0
  39. checkpoint-597/training_args.bin +3 -0
  40. domain_info.txt +4 -0
  41. special_tokens_map.json +30 -0
  42. tokenizer.json +0 -0
  43. tokenizer.model +3 -0
  44. tokenizer_config.json +84 -0
  45. training_info.json +1 -0
README.md ADDED
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+ # Model Card for Fine-Tuned CodeLlama 7B for Text-to-SQL Generation
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+
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+ ## Model Details
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+
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+ - **Base Model**: codellama/CodeLlama-7b-hf
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+ - **Library Name**: peft
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+
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+ ## Model Description
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+
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+ This model is a fine-tuned version of **CodeLlama-7b-hf**, fine-tuned specifically for generating SQL queries from natural language descriptions in the **forestry** domain. It is capable of transforming user queries into SQL commands by using a pre-trained large language model and synthetic text-to-SQL dataset.
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+
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+ **Developed by**: Srishti Rai
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+ **Model Type**: Fine-tuned language model
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+ **Language(s)**: English
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+ **Finetuned from model**: codellama/CodeLlama-7b-hf
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+ **Model Sources**: Fine-tuned on a synthetic text-to-SQL dataset for the forestry domain
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+
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+ ## Uses
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+
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+ ### Direct Use
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+
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+ This model can be used to generate SQL queries for database interactions from natural language descriptions. It is particularly fine-tuned for queries related to forestry and environmental data, including timber production, wildlife habitat, and carbon sequestration.
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+
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+ ### Downstream Use (optional)
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+
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+ This model can also be used in downstream applications where SQL query generation is required, such as:
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+ - Reporting tools that require SQL query generation from user inputs
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+ - Natural language interfaces for database management
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+
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+ ### Out-of-Scope Use
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+
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+ The model is not designed for:
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+ - Tasks outside of SQL query generation, particularly those that require deeper contextual understanding
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+ - Use cases with sensitive or highly regulated data (manual validation of queries is recommended)
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+
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+ ## Bias, Risks, and Limitations
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+
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+ This model may exhibit bias due to the nature of the synthetic data it was trained on. Users should be aware that the model might generate incomplete or incorrect SQL queries. Additionally, the model may struggle with queries that deviate from the patterns seen during training.
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+
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+ ## Recommendations
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+
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+ Users should ensure that generated queries are manually reviewed, especially in critical or sensitive environments, as the model might not always generate accurate SQL statements.
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+
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+ ## How to Get Started with the Model
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+
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+ To get started with the fine-tuned model, use the following code:
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_name = "path_to_your_model_on_kaggle"
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+
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+ # Load model and tokenizer
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+ model = AutoModelForCausalLM.from_pretrained(model_name)
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ # Generate SQL query
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+ input_text = "Your input question here"
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+ inputs = tokenizer(input_text, return_tensors="pt")
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+
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+ # Generate response
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+ outputs = model.generate(
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+ input_ids=inputs["input_ids"],
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+ attention_mask=inputs["attention_mask"],
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+ max_new_tokens=256,
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+ temperature=0.1,
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+ do_sample=False,
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+ pad_token_id=tokenizer.eos_token_id
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+ )
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+
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+ generated_sql = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ print(generated_sql)
adapter_config.json ADDED
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+ "megatron_core": "megatron.core",
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checkpoint-400/README.md ADDED
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+ ---
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+ base_model: codellama/CodeLlama-7b-hf
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+ library_name: peft
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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 0.14.0
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+ "▁<EOT>"
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+ "content": "▁<EOT>",
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+ "▁<EOT>"
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+ "eot_token": "▁<EOT>",
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+ ---
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+ base_model: codellama/CodeLlama-7b-hf
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+ library_name: peft
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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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+ ### 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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+ ## 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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+
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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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+ ## 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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+ <!-- This should link to a Dataset Card if possible. -->
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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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+ [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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+ <!-- 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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+ ## Technical Specifications [optional]
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+ ### Model Architecture and Objective
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+ ### Compute Infrastructure
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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 [optional]
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+ ## Model Card Authors [optional]
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+ ## Model Card Contact
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ "▁<EOT>"
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+ "content": "▁<EOT>",
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+ "▁<EOT>"
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+ "eot_token": "▁<EOT>",
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+ ---
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+ base_model: codellama/CodeLlama-7b-hf
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+ library_name: peft
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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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+ 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
201
+
202
+ - PEFT 0.14.0
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+ "▁<EOT>"
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+ "content": "▁<EOT>",
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+ "▁<EOT>"
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+ "eot_token": "▁<EOT>",
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+ "▁<EOT>"
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+ "content": "▁<EOT>",
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+ "▁<EOT>"
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+ "eot_token": "▁<EOT>",
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