Instructions to use HuggingAnalist/mms300m-asr-lin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingAnalist/mms300m-asr-lin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="HuggingAnalist/mms300m-asr-lin")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("HuggingAnalist/mms300m-asr-lin") model = AutoModelForCTC.from_pretrained("HuggingAnalist/mms300m-asr-lin") - Notebooks
- Google Colab
- Kaggle
MMS-300M โ Lingala ASR
facebook/mms-300m fine-tuned (character CTC head) on WaxalNLP lin_asr for the Waxal ASR challenge. Trained in bf16/fp32 with ctc_zero_infinity=True.
language_model/lm_lin.arpa is a KenLM 4-gram built from the training transcriptions, for beam-search decoding with pyctcdecode (tune alpha/beta on validation).
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