Instructions to use nyralabs/CrisperWhisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyralabs/CrisperWhisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nyralabs/CrisperWhisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nyralabs/CrisperWhisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("nyralabs/CrisperWhisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adds GGML model file (16-bit)
Browse files- ggml-model.bin +3 -0
ggml-model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7dc495cddf564eebf46b9a9515b13cdb059af19a2faac0e06e39b78eeb9302a
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size 3094959366
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