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
Download adapter.asm.bin from facebook/mms-1b-fl102: direct link, hf CLI and curl.
- Browser
- Download file 9.4 MB
-
https://huggingface.co/facebook/mms-1b-fl102/resolve/main/adapter.asm.bin
- Command line
-
hf download hf://facebook/mms-1b-fl102/adapter.asm.bin
-
curl -L -o adapter.asm.bin https://huggingface.co/facebook/mms-1b-fl102/resolve/main/adapter.asm.bin
9.4 MB
- Xet hash:
- 3b719e8b5c53d79a74134877fe28462e5f976999104b512a95dbade963378153
- Size of remote file:
- 9.4 MB
- SHA256:
- aff13e99a3f6b5de035bbae36fbce88a488b38472175aa05e6d27ce90037299b
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