Instructions to use KasuleTrevor/Qwen2-RUNY-Intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KasuleTrevor/Qwen2-RUNY-Intent with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-Audio-7B-Instruct") model = PeftModel.from_pretrained(base_model, "KasuleTrevor/Qwen2-RUNY-Intent") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KasuleTrevor/Qwen2-RUNY-Intent: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/KasuleTrevor/Qwen2-RUNY-Intent/resolve/main/training_args.bin
- Command line
-
hf download hf://KasuleTrevor/Qwen2-RUNY-Intent/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KasuleTrevor/Qwen2-RUNY-Intent/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- d869978b1e405010d7346ce3d46e67099202f68098b910486190825757aaca0d
- Size of remote file:
- 5.84 kB
- SHA256:
- 312a3827e8a335eb1009e2d78901c5c6c6cf4d1992e669ae59dc280a7df51321
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.