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")# pip install -U transformers accelerate # 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
Commit History
-
card: cross-link TEA-ASR-1.1-fmt (numeral-convention variant)
Verified signaturebda08df
-
card: TEA-ASR-1.1-mini row -> v27 numbers
Verified signature344a623 -
TEA-ASR-1.1: 2B second-gen flagship; beats TEA-ASR-1 on all four benchmarks (NTUML2021 6.67, CV19 3.58, ASCEND 9.60, CSZS 10.94; <10h audio, drop-in Qwen3-ASR)
Verified signatureb8188d1 -
initial commit
Verified signatureaca6629