Instructions to use abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178: direct link, hf CLI and curl.
- Browser
- Download file 646 MB
-
https://huggingface.co/abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178/resolve/main/adapter_model.bin
- Command line
-
hf download hf://abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/abaddon182/a6ac489c-f338-4efe-8784-b44bd8056178/resolve/main/adapter_model.bin
646 MB
- Xet hash:
- 22e0fd98fa6b27341b46eb69d24772c08340dd09ef1df2ad100cfeb47fdb36c7
- Size of remote file:
- 646 MB
- SHA256:
- c9059e605aedec5805258598a9bedac84a2fd55f8308d7e4a7e5b6434870f49c
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