Transformers
PyTorch
English
Chinese
speech-processing
empathetic-dialogue
end-to-end-model
spoken-dialogue
Instructions to use ASLP-lab/OSUM-EChat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ASLP-lab/OSUM-EChat with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ASLP-lab/OSUM-EChat", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2543ac9c2eaa271bc311d2ff708bee6309c2dc7f3c683c6a7e1b7a0597e5d1c9
- Size of remote file:
- 6.99 GB
- SHA256:
- 86363b338ce1f84a9ad591e5e8fcfa42c0f9071548375789d70c7a302b4c105d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.