Instructions to use nbninh/6716bef0-46d1-4b0a-84bc-7b7201d23a37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nbninh/6716bef0-46d1-4b0a-84bc-7b7201d23a37 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("defog/llama-3-sqlcoder-8b") model = PeftModel.from_pretrained(base_model, "nbninh/6716bef0-46d1-4b0a-84bc-7b7201d23a37") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fba3aa50cea82765744d4b09370e4808a5b58a39f762963684ce6162392c49b5
- Size of remote file:
- 83.9 MB
- SHA256:
- 49e0c03bb9e51f23cd15c9062c797db2836c6de085b77d85a22ca159409332dd
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