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 optimizer.pt from kosamit/ccbeta-base-clone: direct link, hf CLI and curl.
- Browser
- Download file 311 MB
-
https://huggingface.co/kosamit/ccbeta-base-clone/resolve/main/optimizer.pt
- Command line
-
hf download hf://kosamit/ccbeta-base-clone/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/kosamit/ccbeta-base-clone/resolve/main/optimizer.pt
311 MB
- Xet hash:
- d8c0d0b40d47221d0925a426e0c1a1e2fced2e51515b3f42adbfabc64111252d
- Size of remote file:
- 311 MB
- SHA256:
- da05b16831b1beeb080b87d028982af0c5ddf5649538ef54e45706a27edc5bcc
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