Instructions to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "beast33/38d28935-f58b-4d42-9ecd-9aac981f2592") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from beast33/38d28935-f58b-4d42-9ecd-9aac981f2592: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/resolve/main/training_args.bin
- Command line
-
hf download hf://beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 3030a107cdfada78d45de029066f966d1626a615342e5f811e98fd4efe27abfb
- Size of remote file:
- 6.78 kB
- SHA256:
- 6226fa59c0e439a51dabc555a50050d1e0a947cbd1b461faf8af62a6c6f67417
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