Instructions to use grammatek/icewhisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grammatek/icewhisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="grammatek/icewhisper-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("grammatek/icewhisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("grammatek/icewhisper-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from grammatek/icewhisper-large: direct link, hf CLI and curl.
- Browser
- Download file 6.17 GB
-
https://huggingface.co/grammatek/icewhisper-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://grammatek/icewhisper-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/grammatek/icewhisper-large/resolve/main/flax_model.msgpack
6.17 GB
- Xet hash:
- b5a7ca22b10f82a2ea602f52972382f0af22e6227772ec05528b39c4b075efb8
- Size of remote file:
- 6.17 GB
- SHA256:
- 6a58e72aa99abfc28a54a5a3250ed07e978d5f3740a27d66f09024604891613a
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