Automatic Speech Recognition
Transformers
ONNX
Safetensors
ExecuTorch
English
asr4all
feature-extraction
speech
ctc
streaming
on-device
edge
custom_code
Eval Results (legacy)
Instructions to use futo-org/asr4all-m-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use futo-org/asr4all-m-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="futo-org/asr4all-m-plus", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("futo-org/asr4all-m-plus", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 248 Bytes
216bd23 | 1 2 3 4 5 6 7 8 9 10 | {
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"sampling_rate": 16000,
"padding_value": 0.0,
"padding_side": "right",
"do_normalize": false,
"return_attention_mask": true,
"processor_class": "Wav2Vec2Processor"
} |