Instructions to use PandurangMopgar/LLAMA2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PandurangMopgar/LLAMA2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "PandurangMopgar/LLAMA2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74da20c4b0eb9a45d9e47b9f8864f7dc72e115743421ae9ab0e18a56ad6c3235
- Size of remote file:
- 134 MB
- SHA256:
- 351b77f7f184c94637d5148a44be56b4c31c37a65fce90f96fe540f06160703d
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