Instructions to use sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f/resolve/main/training_args.bin
- Command line
-
hf download hf://sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sn56a6/edf1df8b-bf6c-4fc0-96e6-8e191e0da18f/resolve/main/training_args.bin
6.71 kB
- Xet hash:
- a69be267c82f852ceb966aa5e061351347bbdbe4356a26decc5063c61ecd0093
- Size of remote file:
- 6.71 kB
- SHA256:
- d3189b34fcff7cebbf39836f4a740ff27e8f5e6996466869e83740046bc5d223
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