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  1. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/README.md +202 -0
  2. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/adapter_config.json +29 -0
  3. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/adapter_model.safetensors +3 -0
  4. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/README.md +202 -0
  5. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/adapter_config.json +29 -0
  6. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/adapter_model.safetensors +3 -0
  7. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/optimizer.pt +3 -0
  8. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/rng_state.pth +3 -0
  9. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/scheduler.pt +3 -0
  10. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/special_tokens_map.json +24 -0
  11. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/tokenizer.json +0 -0
  12. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/tokenizer.model +3 -0
  13. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/tokenizer_config.json +0 -0
  14. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/trainer_state.json +140 -0
  15. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-131/training_args.bin +3 -0
  16. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/README.md +202 -0
  17. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/adapter_config.json +29 -0
  18. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/adapter_model.safetensors +3 -0
  19. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/optimizer.pt +3 -0
  20. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/rng_state.pth +3 -0
  21. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/scheduler.pt +3 -0
  22. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/special_tokens_map.json +24 -0
  23. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/tokenizer.json +0 -0
  24. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/tokenizer.model +3 -0
  25. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/tokenizer_config.json +0 -0
  26. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/trainer_state.json +190 -0
  27. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-196/training_args.bin +3 -0
  28. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/README.md +202 -0
  29. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/adapter_config.json +29 -0
  30. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/adapter_model.safetensors +3 -0
  31. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/optimizer.pt +3 -0
  32. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/rng_state.pth +3 -0
  33. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/scheduler.pt +3 -0
  34. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/special_tokens_map.json +24 -0
  35. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/tokenizer.json +0 -0
  36. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/tokenizer.model +3 -0
  37. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/tokenizer_config.json +0 -0
  38. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/trainer_state.json +247 -0
  39. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-262/training_args.bin +3 -0
  40. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/README.md +202 -0
  41. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/adapter_config.json +29 -0
  42. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/adapter_model.safetensors +3 -0
  43. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/optimizer.pt +3 -0
  44. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/rng_state.pth +3 -0
  45. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/scheduler.pt +3 -0
  46. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/special_tokens_map.json +24 -0
  47. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/tokenizer.json +0 -0
  48. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/tokenizer.model +3 -0
  49. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/tokenizer_config.json +0 -0
  50. Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/checkpoint-327/trainer_state.json +297 -0
Mistral-7B-Instruct-v0.3_int4_flare-en-fpb_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.3-num-930-sd-4/README.md ADDED
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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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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+ ## 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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+ [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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+ [More Information Needed]
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+
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+ ### Results
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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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+ ## 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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+
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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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+ [More Information Needed]
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+ ### Compute Infrastructure
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+ [More Information Needed]
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+
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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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+
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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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+
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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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+ - PEFT 0.13.1
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+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
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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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+ 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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+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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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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+ <!-- 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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+ ## Bias, Risks, and Limitations
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+ ### Recommendations
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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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+ ## Training Details
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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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+ ## Technical Specifications [optional]
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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 0.13.1
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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+ library_name: peft
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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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+ ## 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
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+
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+ - PEFT 0.13.1
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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+ ### Framework versions
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+ - PEFT 0.13.1
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