Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results
Instructions to use openai/whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Fix error in config.json
#9
by pere - opened
- config.json +1 -1
config.json
CHANGED
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@@ -18,7 +18,7 @@
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"decoder_ffn_dim": 5120,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 32,
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-
"decoder_start_token_id":
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"dropout": 0.0,
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"encoder_attention_heads": 20,
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"encoder_ffn_dim": 5120,
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| 18 |
"decoder_ffn_dim": 5120,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 32,
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+
"decoder_start_token_id": 50258,
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"dropout": 0.0,
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| 23 |
"encoder_attention_heads": 20,
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| 24 |
"encoder_ffn_dim": 5120,
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