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
Upload prompt.wav with huggingface_hub
Browse files- .gitattributes +1 -0
- prompt.wav +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
prompt.wav filter=lfs diff=lfs merge=lfs -text
|
prompt.wav
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:75c27705b1b29ca325cd11e3f693b1baf3fb7a1cc97679b7d83df15f2e64b369
|
| 3 |
+
size 893702
|