Instructions to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_chatGPT_temp0_Seed110 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_chatGPT_temp0_Seed110 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_chatGPT_temp0_Seed110") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8910bd6d6e6c65e709188629064cbce45eadee71ba8b5d3912b5a6a51327f7c5
- Size of remote file:
- 67.2 MB
- SHA256:
- ce35e23cfa955eed0c80cfcca0adb146554792ff64da9528ff7b50eaf2ad3679
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