Instructions to use dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b: direct link, hf CLI and curl.
- Browser
- Download file 55.2 kB
-
https://huggingface.co/dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/adapter_model.bin
55.2 kB
- Xet hash:
- ee604b4603d502de917510bddac5b4c319274e4721d9790252b4a7a6121d8aa8
- Size of remote file:
- 55.2 kB
- SHA256:
- 724af06f58d99e088fafa1a3280c342568308d402612abdbfb9f9d8dbaac63b0
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