Instructions to use adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444/resolve/main/adapter_model.bin
- Command line
-
hf download hf://adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/adammandic87/9a357cf7-cdaf-4647-9ab1-85fe2f251444/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- 9913ee5890ddd116e1dd5ae0db7166c2c1645b959a6f9b30faa0264a49f79eeb
- Size of remote file:
- 84 MB
- SHA256:
- ab471316b15181627338047fb165ede44a04244e894316040aef8d810c76acb1
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