Feature Extraction
Transformers
English
audio-text-retrieval
audio-retrieval
clap
multimodal-llm
lora
acl2026
Instructions to use JudeJiwoo/OEA-Qwen3B-Cl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JudeJiwoo/OEA-Qwen3B-Cl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="JudeJiwoo/OEA-Qwen3B-Cl")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JudeJiwoo/OEA-Qwen3B-Cl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download step_40.pt from JudeJiwoo/OEA-Qwen3B-Cl: direct link, hf CLI and curl.
- Browser
- Download file 9.47 GB
-
https://huggingface.co/JudeJiwoo/OEA-Qwen3B-Cl/resolve/main/step_40.pt
- Command line
-
hf download hf://JudeJiwoo/OEA-Qwen3B-Cl/step_40.pt
-
curl -L -o step_40.pt https://huggingface.co/JudeJiwoo/OEA-Qwen3B-Cl/resolve/main/step_40.pt
9.47 GB
- Xet hash:
- 5d7641e99cc8984976f51f59a945ef214080ca27324010947c40a89299e22848
- Size of remote file:
- 9.47 GB
- SHA256:
- d5f2648c19b07fe5b33c22873098f9b9d749dfe2fb48e5d3dedfcea827c39b5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.