Instructions to use benahi/hidegpv4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use benahi/hidegpv4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Meta-Llama-3.1-8B-Instruct-Reference__TOG__FT") model = PeftModel.from_pretrained(base_model, "benahi/hidegpv4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c668b5abb3609d800a2f8dc67cb346852956804ef73ff728299a13955de19301
- Size of remote file:
- 83.9 MB
- SHA256:
- 23e4f9e51e778008b32ebdf3c4e075b58b382643131657175382e6dcbbabfd8b
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