Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
English
wav2vec2
audio
hf-asr-leaderboard
mozilla-foundation/common_voice_6_0
robust-speech-event
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use jonatasgrosman/wav2vec2-large-xlsr-53-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/wav2vec2-large-xlsr-53-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-english")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-english") model = AutoModelForCTC.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-english", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
7f6f8d5
1
Parent(s): 726deeb
update config
Browse files- config.json +0 -1
config.json
CHANGED
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"feat_extract_norm": "layer",
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"feat_proj_dropout": 0.05,
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"final_dropout": 0.0,
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"gradient_checkpointing": true,
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"hidden_act": "gelu",
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"hidden_dropout": 0.05,
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"hidden_size": 1024,
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"feat_extract_norm": "layer",
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"feat_proj_dropout": 0.05,
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"final_dropout": 0.0,
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"hidden_act": "gelu",
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"hidden_dropout": 0.05,
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"hidden_size": 1024,
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