Instructions to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9521e7e3f284f933dcc5bd785712d153dcda407cc78bc5a0a17bd4a347abecdf
- Size of remote file:
- 83.9 MB
- SHA256:
- 8a0298fa03b6f9ef298819294e20227e7be140566702992ec2d2ab530eb8dd11
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