Instructions to use behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_chatGPT_temp0_Seed115 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_Seed115 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_Seed115") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd3e0da04d5c25b5f070ea4e16b70133ac2de6d838bb8cbcfa1eedc8fc692962
- Size of remote file:
- 67.2 MB
- SHA256:
- d52f29ab8f20932fa56a36852ca7e1147726386c3d2799c7b1629b16fe9b837a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.