Instructions to use yxdu/mcat-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yxdu/mcat-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yxdu/mcat-large")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yxdu/mcat-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add comprehensive model card for MCAT
#1
by nielsr HF Staff - opened
This PR adds a comprehensive model card for the MCAT model, based on the paper MCAT: Scaling Many-to-Many Speech-to-Text Translation with MLLMs to 70 Languages.
The update includes:
- Relevant metadata such as
license,pipeline_tag,library_name,tags, andbase_model. - Links to the paper and the GitHub repository.
- A brief description of the model and its capabilities.
- Detailed installation, model download, and inference demo instructions from the GitHub README.
Please review and merge if everything looks good.
yxdu changed pull request status to merged