Instructions to use abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b/resolve/05a686192decd119bc4b77c76d710f61250af80a/training_args.bin
- Command line
-
hf download hf://abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b@05a686192decd119bc4b77c76d710f61250af80a/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/abaddon182/b2e8e170-9aed-4112-bd28-3241f0b9678b/resolve/05a686192decd119bc4b77c76d710f61250af80a/training_args.bin
6.84 kB
- Xet hash:
- 524a817d32a2adbfac1290d3150566f9664a18559d29186fe20d2194f151a23e
- Size of remote file:
- 6.84 kB
- SHA256:
- ac28cc4ecf94998eab320b2ee97931ed0a4ed515fe262ef69de07e3c9ad083de
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