Instructions to use facebook/mms-1b-fl102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-fl102 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-fl102")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-fl102") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-fl102", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Change the model's name to differentiate it from "mms-1b-all". (#4)
- Change the model's name to differentiate it from "mms-1b-all". (49aa6ff22b957d7e33587294cdbb994c1d5bce78) Co-authored-by: Mohamed Aymane Farhi <ayymen@users.noreply.huggingface.co>d483345
-
Change the license (#1)
- Change the license (863ce0d8842d34fd099e2e449184407b27525d91) Co-authored-by: Wannaphong Phatthiyaphaibun <wannaphong@users.noreply.huggingface.co>de665fe
-
correct vocab
d7f6da1 -
correct vocab
4210646 -
correct vocab
a87fbc3 -
correct vocab
aa658c8
-
Merge branch 'main' of https://huggingface.co/patrickvonplaten/mms-1b-fl102
5db035c -
finish
32f8755
-
Update README.md
2301d1d -
Create README.md
b330d8b -
upload weights
f3e9673 -
initial commit
06b7bd1