Automatic Speech Recognition
Transformers
Safetensors
English
moonshine
quantization-aware-training
int8
riscv
edge
Instructions to use CobbledSteel/moonshine-tiny-qat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CobbledSteel/moonshine-tiny-qat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CobbledSteel/moonshine-tiny-qat")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CobbledSteel/moonshine-tiny-qat") model = AutoModelForSpeechSeq2Seq.from_pretrained("CobbledSteel/moonshine-tiny-qat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CobbledSteel/moonshine-tiny-qat: direct link, hf CLI and curl.
- Browser
- Download file 1.99 MB
-
https://huggingface.co/CobbledSteel/moonshine-tiny-qat/resolve/main/tokenizer.json
- Command line
-
hf download hf://CobbledSteel/moonshine-tiny-qat/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/CobbledSteel/moonshine-tiny-qat/resolve/main/tokenizer.json
1.99 MB
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