Instructions to use kosamit/ccbeta-large-clone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kosamit/ccbeta-large-clone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kosamit/ccbeta-large-clone")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kosamit/ccbeta-large-clone") model = AutoModelForSpeechSeq2Seq.from_pretrained("kosamit/ccbeta-large-clone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from kosamit/ccbeta-large-clone: direct link, hf CLI and curl.
- Browser
- Download file 3.51 GB
-
https://huggingface.co/kosamit/ccbeta-large-clone/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://kosamit/ccbeta-large-clone@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/kosamit/ccbeta-large-clone/resolve/refs%2Fpr%2F1/optimizer.pt
3.51 GB
- Xet hash:
- 6771956d587250cefbdc43accdf5142764bb0fbaa38f7dfb6d9c2029cc1d6a49
- Size of remote file:
- 3.51 GB
- SHA256:
- 1538281549dc76c5e6125641add53593bb30771e09a3485fd4f828f03640acca
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