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 training_args.bin from dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/training_args.bin
- Command line
-
hf download hf://dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 1c82dc5e8aa6c0153f7683a936c7a6a5345e6bf408ce4987bafbbfbce0f7aec1
- Size of remote file:
- 6.84 kB
- SHA256:
- c6393756cde6300e3bc737cb13b04761a6ca53fb7bee11908d9cd5e284f70f93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.