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 pytorch_model.bin from kosamit/ccbeta-large-clone: direct link, hf CLI and curl.
- Browser
- Download file 6.17 GB
-
https://huggingface.co/kosamit/ccbeta-large-clone/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kosamit/ccbeta-large-clone/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kosamit/ccbeta-large-clone/resolve/main/pytorch_model.bin
6.17 GB
- Xet hash:
- 7fd3ad3248836b924acd12babe9d7e9a6774cebb77fdcbf637278eea3a1ae10c
- Size of remote file:
- 6.17 GB
- SHA256:
- 94a8ab461227ddc1e280bfb24fd4a53f729a3f6731123809efa0c6396f80d55e
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