Automatic Speech Recognition
Transformers
Safetensors
Welsh
English
moonshine
welsh
speech-recognition
vocabulary-pruning
Eval Results (legacy)
Instructions to use rebreda/moonshine-tiny-welsh-pruned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rebreda/moonshine-tiny-welsh-pruned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rebreda/moonshine-tiny-welsh-pruned")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rebreda/moonshine-tiny-welsh-pruned") model = AutoModelForSpeechSeq2Seq.from_pretrained("rebreda/moonshine-tiny-welsh-pruned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Upload moonshine-tiny-welsh-pruned: weights, tokenizer, config and model card
bac3a13 verified Download tokenizer.json from rebreda/moonshine-tiny-welsh-pruned: direct link, hf CLI and curl.
- Browser
- Download file 1.46 MB
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https://huggingface.co/rebreda/moonshine-tiny-welsh-pruned/resolve/main/tokenizer.json
- Command line
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hf download hf://rebreda/moonshine-tiny-welsh-pruned/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/rebreda/moonshine-tiny-welsh-pruned/resolve/main/tokenizer.json
1.46 MB
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