Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use futureProofGlitch/whisper-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use futureProofGlitch/whisper-small-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="futureProofGlitch/whisper-small-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("futureProofGlitch/whisper-small-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("futureProofGlitch/whisper-small-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4a0ea4dc023781d0ffbbcd2d283e1aa9936d55f0f0af1c2335f101011d33632
- Size of remote file:
- 5.05 kB
- SHA256:
- ed67f28daf3864cd4fcc07b22d5be46b0932aebd6984aca81343eff2e0af9090
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