Instructions to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_GroundTruth_seed101 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_GroundTruth_seed101 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_GroundTruth_seed101") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85c06265b177aa659be1cce687ae64a5828c59c85e354781e4271c455cd7d3e8
- Size of remote file:
- 33.6 MB
- SHA256:
- 8087b4291e53115974d04ea19bdd0fdb71a3d233cbde307168052443d10e4e35
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