Automatic Speech Recognition
Transformers
Safetensors
fun_asr_nano
text-generation
speech-recognition
asr
end-to-end
multilingual
streaming
arxiv:2407.04051
Instructions to use FunAudioLLM/Fun-ASR-Nano-2512-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FunAudioLLM/Fun-ASR-Nano-2512-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="FunAudioLLM/Fun-ASR-Nano-2512-hf")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("FunAudioLLM/Fun-ASR-Nano-2512-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: clarify Transformers checkpoint CTC capability boundary
Browse files
README.md
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Fun-ASR-Nano is an end-to-end speech recognition model by [FunAudioLLM](https://github.com/FunAudioLLM), trained on tens of millions of hours of real speech data. This checkpoint supports Chinese, English, and Japanese; its Chinese coverage includes 7 dialect groups and 26 regional accents. For 31-language recognition, use the separate [Fun-ASR-MLT-Nano-2512](https://huggingface.co/FunAudioLLM/Fun-ASR-MLT-Nano-2512) checkpoint.
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## Transformers quickstart
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Fun-ASR-Nano support is being added to Transformers in [huggingface/transformers#46180](https://github.com/huggingface/transformers/pull/46180). Until it is included in a Transformers release, use a build containing that PR.
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Fun-ASR-Nano is an end-to-end speech recognition model by [FunAudioLLM](https://github.com/FunAudioLLM), trained on tens of millions of hours of real speech data. This checkpoint supports Chinese, English, and Japanese; its Chinese coverage includes 7 dialect groups and 26 regional accents. For 31-language recognition, use the separate [Fun-ASR-MLT-Nano-2512](https://huggingface.co/FunAudioLLM/Fun-ASR-MLT-Nano-2512) checkpoint.
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## Capability boundary
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This Transformers checkpoint is for generation-based transcription. It does not include the native CTC branch, so it does not provide CTC-dependent timestamps or speaker diarization. For those capabilities, use the [original checkpoint](https://huggingface.co/FunAudioLLM/Fun-ASR-Nano-2512) through [FunASR](https://github.com/modelscope/FunASR) or its native vLLM integration.
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## Transformers quickstart
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Fun-ASR-Nano support is being added to Transformers in [huggingface/transformers#46180](https://github.com/huggingface/transformers/pull/46180). Until it is included in a Transformers release, use a build containing that PR.
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