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--- |
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base_model: unsloth/Meta-Llama-3.1-8B-bnb-4bit |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- llama |
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- trl |
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- sft |
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datasets: |
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- emessy/flash_fiction_1 |
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--- |
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# Uploaded model |
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- **Developed by:** emessy |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/Meta-Llama-3.1-8B-bnb-4bit |
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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# Configure LoRA |
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lora_config = LoraConfig( |
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r=16, |
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lora_alpha=16, |
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target_modules=["q_proj", "k_proj", "v_proj", "o_proj"], |
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lora_dropout=0.05, |
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bias="none", |
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task_type="CAUSAL_LM" |
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) |
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# Training arguments |
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training_args = TrainingArguments( |
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output_dir="./results", |
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num_train_epochs=5, |
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per_device_train_batch_size=4, |
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gradient_accumulation_steps=4, |
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learning_rate=2e-4, |
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fp16=True, # Use half-precision |
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logging_steps=10, |
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save_steps=50, |
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eval_steps=50, |
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) |
