Instructions to use mispeech/dasheng-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/dasheng-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/dasheng-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mispeech/dasheng-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 518 Bytes
083f870 c314ac7 5835415 c314ac7 083f870 | 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 | {
"architectures": [
"DashengModel"
],
"auto_map": {
"AutoConfig": "configuration_dasheng.DashengConfig",
"AutoModel": "modeling_dasheng.DashengModel"
},
"encoder_kwargs": {
"depth": 12,
"embed_dim": 768,
"num_heads": 12,
"patch_size": [
64,
4
],
"patch_stride": [
64,
4
],
"target_length": 1008
},
"loss": "BCELoss",
"model_type": "dasheng",
"name": "dasheng-base",
"torch_dtype": "float32",
"transformers_version": "4.35.2"
}
|