Instructions to use CLiC-UB/Casper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLiC-UB/Casper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CLiC-UB/Casper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CLiC-UB/Casper") model = AutoModelForSpeechSeq2Seq.from_pretrained("CLiC-UB/Casper") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:19ab336e2971c9cd68e8fe7d4a80f34f543ae498518d864f844a74cf0abc2f91
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size 966995080
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