Automatic Speech Recognition
Transformers
Safetensors
Chinese
English
ming_v3_asr
text-generation
audio
speech-recognition
contextual-asr
custom_code
Instructions to use ml-resources/Ming-3.0-asr-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml-resources/Ming-3.0-asr-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ml-resources/Ming-3.0-asr-tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ml-resources/Ming-3.0-asr-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 670 Bytes
4c0600d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"feature_extractor_type": "MingV3ASRFeatureExtractor",
"processor_class": "MingV3ASRProcessor",
"feature_size": 128,
"sampling_rate": 16000,
"padding_value": 0.0,
"audio_config": {
"n_mels": 128,
"n_audio_ctx": 3000,
"n_audio_state": 1280,
"n_audio_head": 20,
"n_audio_layer": 32,
"downsampler_kernel_size_list": [
3
],
"downsampler_stride_list": [
2
],
"chunk_frames": 3000,
"downsampler_padding_list": [
1
]
},
"auto_map": {
"AutoFeatureExtractor": "feature_extraction_ming_v3_asr.MingV3ASRFeatureExtractor",
"AutoProcessor": "processing_ming_v3_asr.MingV3ASRProcessor"
}
}
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