Instructions to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_chatGPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_chatGPT2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Trelis/Llama-2-7b-chat-hf-sharded-bf16") model = PeftModel.from_pretrained(base_model, "behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_chatGPT2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c7d464e62adb79f1ebd81b4d0385c9d5d9991dfa5300dc55db6544098ee58a6
- Size of remote file:
- 33.6 MB
- SHA256:
- 7172827f77e7f20d3c1243e40e5cb3d6a1434f8bb1edd4e628d949bc3b934c2e
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