Instructions to use kosamit/ccbeta-base-clone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kosamit/ccbeta-base-clone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kosamit/ccbeta-base-clone")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kosamit/ccbeta-base-clone") model = AutoModelForSpeechSeq2Seq.from_pretrained("kosamit/ccbeta-base-clone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kosamit/ccbeta-base-clone: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/kosamit/ccbeta-base-clone/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kosamit/ccbeta-base-clone/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kosamit/ccbeta-base-clone/resolve/main/pytorch_model.bin
290 MB
- Xet hash:
- bae4e91d831f4b9e5127ba2a5f1d3f9c5b6ce699325651fdba82a8db2d53a185
- Size of remote file:
- 290 MB
- SHA256:
- 8de507d695477b654babd01166239440f4fe7b5ade23390df6be035cbbe486dd
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