Instructions to use scribe-project/wav2vec2-large-voxrex-300m-radio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scribe-project/wav2vec2-large-voxrex-300m-radio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="scribe-project/wav2vec2-large-voxrex-300m-radio")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio") model = AutoModelForCTC.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from scribe-project/wav2vec2-large-voxrex-300m-radio: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/scribe-project/wav2vec2-large-voxrex-300m-radio/resolve/92dcc0109200efe1baa00dec55f7b672a8267e3a/pytorch_model.bin
- Command line
-
hf download hf://scribe-project/wav2vec2-large-voxrex-300m-radio@92dcc0109200efe1baa00dec55f7b672a8267e3a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/scribe-project/wav2vec2-large-voxrex-300m-radio/resolve/92dcc0109200efe1baa00dec55f7b672a8267e3a/pytorch_model.bin
1.26 GB
- Xet hash:
- 44f0d1b005f057d8f938f94af6834f2ad3e17b94d6d8352533999d95b56e1edb
- Size of remote file:
- 1.26 GB
- SHA256:
- cd9f90f2b7a189658855c8577b7dacc864fc47bb0415d98b7fea4985e2ffdd7a
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