Instructions to use 52100303-TranPhuocSang/vilawllama3-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 52100303-TranPhuocSang/vilawllama3-q4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "52100303-TranPhuocSang/vilawllama3-q4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2fe410c82492840e1c4766541c45d54b13b6bede4341272bdf8844a0a69cb6f
- Size of remote file:
- 671 MB
- SHA256:
- ca6892518b24d84f27d0315e37003c063e4f288f663cfe7679bfed73710225ae
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