Automatic Speech Recognition
Transformers
Safetensors
Chinese
English
qwen3_asr
taiwan-mandarin
traditional-chinese
code-switching
qwen3-asr
speech
Instructions to use JacobLinCool/TEA-ASR-1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JacobLinCool/TEA-ASR-1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JacobLinCool/TEA-ASR-1.1")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JacobLinCool/TEA-ASR-1.1") model = AutoModelForMultimodalLM.from_pretrained("JacobLinCool/TEA-ASR-1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 436 Bytes
b8188d1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"base": "Qwen/Qwen3-ASR-1.7B",
"adapter": "outputs/tea11_17b_v6_r_s0",
"selected_row_delta": null,
"selected_row_summary": null,
"decode_config": "s2tw",
"tokenizer_stats": {
"clean": 150482,
"marked": 1161,
"merges": [
151387,
138969
]
},
"verification": {
"checked_sequences": 152643,
"decode_mismatches": 0,
"sentinel_leaks": 0,
"examples": [],
"is_fast": true
}
}
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