Instructions to use Rupak100/Fine_Tuining_Scoring with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rupak100/Fine_Tuining_Scoring with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("abhishek/llama-2-7b-hf-small-shards") model = PeftModel.from_pretrained(base_model, "Rupak100/Fine_Tuining_Scoring") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f036230b99f16e25496914fc7b8ffa5ed7568ee3f13d402f4fe0d1fde8a4952
- Size of remote file:
- 33.6 MB
- SHA256:
- 6dc1638bb4325d10a50dd9105b362f8abb110dd03c9602545221fed62bca6105
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