Instructions to use skar01/llama2-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use skar01/llama2-coder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyPixel/Llama-2-7B-bf16-sharded") model = PeftModel.from_pretrained(base_model, "skar01/llama2-coder") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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---
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## Training procedure
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Llama2 (7B) model fine-tuned on the CodeAlpaca 20k instructions dataset by using the method QLoRA with PEFT library.
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Training and evaluation data 📚
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CodeAlpaca_20K: contains 20K instruction-following data used for fine-tuning the Code Alpaca model.
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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