Instructions to use mediaProcessing/Transcriber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mediaProcessing/Transcriber with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mediaProcessing/Transcriber")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mediaProcessing/Transcriber") model = AutoModelForMultimodalLM.from_pretrained("mediaProcessing/Transcriber") - 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:a1b2971d71942a15d3b77ab4228c601d335f6c451f0f1202ec73995108dfee81
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size 966995080
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