Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
English
speech_to_text
speech
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use Classroom-workshop/assignment1-francesco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Classroom-workshop/assignment1-francesco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Classroom-workshop/assignment1-francesco")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Classroom-workshop/assignment1-francesco") model = AutoModelForSpeechSeq2Seq.from_pretrained("Classroom-workshop/assignment1-francesco") - Notebooks
- Google Colab
- Kaggle
File size: 242 Bytes
15eb754 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"do_ceptral_normalize": true,
"feature_size": 80,
"normalize_means": true,
"normalize_vars": true,
"num_mel_bins": 80,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
}
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