Instructions to use joaoalvarenga/model-sid-voxforge-cetuc-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaoalvarenga/model-sid-voxforge-cetuc-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joaoalvarenga/model-sid-voxforge-cetuc-0")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("joaoalvarenga/model-sid-voxforge-cetuc-0") model = AutoModelForCTC.from_pretrained("joaoalvarenga/model-sid-voxforge-cetuc-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from joaoalvarenga/model-sid-voxforge-cetuc-0: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/joaoalvarenga/model-sid-voxforge-cetuc-0/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://joaoalvarenga/model-sid-voxforge-cetuc-0@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/joaoalvarenga/model-sid-voxforge-cetuc-0/resolve/refs%2Fpr%2F1/flax_model.msgpack
1.26 GB
- Xet hash:
- 01fe046df681008112ca39c5721832c1b425dd90323d7ec51679c98bce79bf38
- Size of remote file:
- 1.26 GB
- SHA256:
- 71b1e8bbc38c4bf9c08a573111668bfa37b8aeac8da9365b909ceddf31555ffb
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