Instructions to use Gigworks/ASR_id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gigworks/ASR_id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Gigworks/ASR_id")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Gigworks/ASR_id") model = AutoModelForCTC.from_pretrained("Gigworks/ASR_id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Gigworks/ASR_id: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Gigworks/ASR_id/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Gigworks/ASR_id/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Gigworks/ASR_id/resolve/main/flax_model.msgpack
1.26 GB
- Xet hash:
- 599aa66eec0cff89be314bfee771ec08fe28a43cab152662b398cb5f683d4b03
- Size of remote file:
- 1.26 GB
- SHA256:
- 46a5f28dc921d23559b268be8708b451ac8206e65a2de60f12a1813c8595a22e
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