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")# 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.fra.bin from facebook/mms-1b-fl102: direct link, hf CLI and curl.
- Browser
- Download file 9.14 MB
-
https://huggingface.co/facebook/mms-1b-fl102/resolve/main/adapter.fra.bin
- Command line
-
hf download hf://facebook/mms-1b-fl102/adapter.fra.bin
-
curl -L -o adapter.fra.bin https://huggingface.co/facebook/mms-1b-fl102/resolve/main/adapter.fra.bin
9.14 MB
- Xet hash:
- 8157427127aeac91b73c157857683d7d4d05719983d13300a4f3e7d4386c1292
- Size of remote file:
- 9.14 MB
- SHA256:
- 54189301808029020ace908f7cc3771c6d5679c0e3da6ed59b8a579435cbcf30
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