Instructions to use fuyingw/MELP_Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fuyingw/MELP_Encoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fuyingw/MELP_Encoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card for MELP: add paper link, description, and pipeline tag
#1
by nielsr HF Staff - opened
This PR improves the model card for the MELP model by:
- Adding the
pipeline_tag: audio-text-to-textto the metadata, ensuring the model can be found at https://huggingface.co/models?pipeline_tag=audio-text-to-text. - Populating the model description and direct use cases with information from the paper abstract.
- Adding a direct link to the paper at https://huggingface.co/papers/2506.21803.
- Adding the
license: apache-2.0to the metadata. - Including a basic
transformersusage example. - Adding the BibTeX and APA citations for the paper.
Please review and merge.
fuyingw changed pull request status to merged