Instructions to use cwaud/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cwaud/test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "cwaud/test") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cwaud/test: direct link, hf CLI and curl.
- Browser
- Download file 148 MB
-
https://huggingface.co/cwaud/test/resolve/refs%2Fpr%2F1/adapter_model.bin
- Command line
-
hf download hf://cwaud/test@refs/pr/1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cwaud/test/resolve/refs%2Fpr%2F1/adapter_model.bin
148 MB
- Xet hash:
- 11502f42461971144ec174c6f0b595e8b2ebfee5fd656ebbae10eaf744e3966c
- Size of remote file:
- 148 MB
- SHA256:
- 10bcf26de16460ea687e7cfc6f7e062ae9abe8c5db8e4176332c9788a3bcf1b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.