Instructions to use NoobCoder10/Scoring_V_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NoobCoder10/Scoring_V_1 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, "NoobCoder10/Scoring_V_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f830263b2bc1547d7c4490ba0fdfe49e786c771866feeb6dc6cbd3cd8b4447d
- Size of remote file:
- 7.56 GB
- SHA256:
- b9cf33854d955d9eda983600882ae0179d96e1dd12b36ef899c96abd5aa3b02e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.