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
card: cross-link TEA-ASR-1.1-fmt (numeral-convention variant)
Browse files
README.md
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benchmark**. A companion **TEA-ASR-1.1-mini** shares the recipe at 780M — see
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[`JacobLinCool/TEA-ASR-1.1-mini`](https://huggingface.co/JacobLinCool/TEA-ASR-1.1-mini).
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## What's new in 1.1
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- 🔀 **Code-switch leap** — ASCEND 10.59 → **9.60**, CSZS 10.98 → **10.94**; the English side of code-switch
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benchmark**. A companion **TEA-ASR-1.1-mini** shares the recipe at 780M — see
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[`JacobLinCool/TEA-ASR-1.1-mini`](https://huggingface.co/JacobLinCool/TEA-ASR-1.1-mini).
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> **Need a controllable numeral style?** The
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> [`TEA-ASR-1.1-fmt`](https://huggingface.co/JacobLinCool/TEA-ASR-1.1-fmt) variant adds a verified
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> numeral-convention dial (`digits` 108年 / `zh-num` 一百零八年) for formatting-sensitive,
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> Mandarin-dominant use, trading a small measured amount of dense-code-switch robustness. This
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> flagship stays the best pick for recognition quality and heavy code-switching.
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## What's new in 1.1
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- 🔀 **Code-switch leap** — ASCEND 10.59 → **9.60**, CSZS 10.98 → **10.94**; the English side of code-switch
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