Instructions to use haohaa/wav2vec2-large-mms-1b-shan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haohaa/wav2vec2-large-mms-1b-shan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="haohaa/wav2vec2-large-mms-1b-shan")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("haohaa/wav2vec2-large-mms-1b-shan") model = AutoModelForCTC.from_pretrained("haohaa/wav2vec2-large-mms-1b-shan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from haohaa/wav2vec2-large-mms-1b-shan: direct link, hf CLI and curl.
- Browser
- Download file 34 Bytes
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https://huggingface.co/haohaa/wav2vec2-large-mms-1b-shan/resolve/main/added_tokens.json
- Command line
-
hf download hf://haohaa/wav2vec2-large-mms-1b-shan/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/haohaa/wav2vec2-large-mms-1b-shan/resolve/main/added_tokens.json
34 Bytes
| { | |
| "</s>": 43, | |
| "<s>": 42 | |
| } | |