Instructions to use yxdu/ESRT-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yxdu/ESRT-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yxdu/ESRT-4B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yxdu/ESRT-4B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add metadata and improve model card
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
This PR improves the model card by adding metadata for the library_name and pipeline_tag to ensure the model is discoverable and categorized correctly. I have also included direct links to the paper and the official GitHub repository for better documentation.
yxdu changed pull request status to merged