Instructions to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_SystemError0percentSeed100 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_SystemError0percentSeed100 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_SystemError0percentSeed100") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e0d205c50f823ae7aadfa66d380db114364d04da7b53e20d19da3e20048bde0
- Size of remote file:
- 67.2 MB
- SHA256:
- 0720f0ebd431a87617ec510873661837add6f92f6b32ba58a4942d9c615dc7b0
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