Instructions to use prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d/resolve/main/training_args.bin
- Command line
-
hf download hf://prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prxy5608/2bdb490c-a538-4890-95be-985b5a34cc6d/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 47d693d2a110d04186a97b2a6a3ff727016ab6004978717a342039c3cae2ab8b
- Size of remote file:
- 6.84 kB
- SHA256:
- 06ac2b9b78d4b4462b282735581de6bdca4aed0bba52449b722a218bf91c7c5a
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