Automatic Speech Recognition
Transformers
Safetensors
zero_swot_encoder
feature-extraction
zeroswot
speech translation
zero-shot
end-to-end
nllb
wav2vec2
custom_code
Instructions to use johntsi/ZeroSwot-Medium_asr-mustc_en-to-200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use johntsi/ZeroSwot-Medium_asr-mustc_en-to-200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="johntsi/ZeroSwot-Medium_asr-mustc_en-to-200", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("johntsi/ZeroSwot-Medium_asr-mustc_en-to-200", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 735 Bytes
b19206a | 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 | {
"_name_or_path": "johntsi/ZeroSwot-Medium_asr-mustc_en-to-200/model.safetensors",
"architectures": [
"ZeroSwotEncoderModel"
],
"auto_map": {
"AutoConfig": "model.ZeroSwotEncoderConfig",
"AutoModel": "model.ZeroSwotEncoderModel"
},
"compression_adapter": {
"blank_idx": 0,
"dropout": 0.1,
"embed_dim": 1024,
"sep_idx": 4,
"transformer_layers": 3
},
"embed_dim": 1024,
"model_type": "zero_swot_encoder",
"nllb_model_name_or_path": "facebook/nllb-200-distilled-600M",
"speech_embedder": {
"nllb_eng_id": 256047,
"nllb_eos_id": 2
},
"torch_dtype": "float32",
"transformers_version": "4.41.2",
"wav2vec2_model_name_or_path": "facebook/wav2vec2-large-960h-lv60-self"
}
|