Instructions to use airesearch/Qwen3-30B-A3B-medqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use airesearch/Qwen3-30B-A3B-medqa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/project/lt200252-wcbart/pumet/models/Qwen3-30B-A3B") model = PeftModel.from_pretrained(base_model, "airesearch/Qwen3-30B-A3B-medqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aca723a25e2d7900eb5f2d2124d3194ea37d91e57c11cfcf319d83ee17906579
- Size of remote file:
- 5 GB
- SHA256:
- 3e346efaa3a2a665b06b424e34711768fd4b346506eaac5725e02075c3cf3012
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.