From 9ba0dbd98bf69c830dfcfde8f109a400cb65e4e5 Mon Sep 17 00:00:00 2001 From: 雾聪 <wucong.lyb@alibaba-inc.com> Date: 星期五, 29 三月 2024 17:24:59 +0800 Subject: [PATCH] fix func Forward --- README.md | 69 ++++++++++++++++++++++++++-------- 1 files changed, 52 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index d436d5e..38fd686 100644 --- a/README.md +++ b/README.md @@ -27,7 +27,9 @@ <a name="whats-new"></a> ## What's new: -- 2024/03/03: Offline File Transcription Service 4.4, Offline File Transcription Service of English 1.5锛孯eal-time Transcription Service 1.9 released锛孌ocker image supports ARM64 platform锛�([docs](runtime/readme.md)) +- 2024/03/05锛欰dded the Qwen-Audio and Qwen-Audio-Chat large-scale audio-text multimodal models, which have topped multiple audio domain leaderboards. These models support speech dialogue, [usage](examples/industrial_data_pretraining/qwen_audio). +- 2024/03/05锛欰dded support for the Whisper-large-v3 model, a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. It can be downloaded from the[modelscope](examples/industrial_data_pretraining/whisper/demo.py), and [openai](examples/industrial_data_pretraining/whisper/demo_from_openai.py). +- 2024/03/05: Offline File Transcription Service 4.4, Offline File Transcription Service of English 1.5锛孯eal-time Transcription Service 1.9 released锛宒ocker image supports ARM64 platform, update modelscope锛�([docs](runtime/readme.md)) - 2024/01/30锛歠unasr-1.0 has been released ([docs](https://github.com/alibaba-damo-academy/FunASR/discussions/1319)) - 2024/01/30锛歟motion recognition models are new supported. [model link](https://www.modelscope.cn/models/iic/emotion2vec_base_finetuned/summary), modified from [repo](https://github.com/ddlBoJack/emotion2vec). - 2024/01/25: Offline File Transcription Service 4.2, Offline File Transcription Service of English 1.3 released锛宱ptimized the VAD (Voice Activity Detection) data processing method, significantly reducing peak memory usage, memory leak optimization; Real-time Transcription Service 1.7 released锛宱ptimizatized the client-side锛�([docs](runtime/readme.md)) @@ -67,20 +69,23 @@ ## Model Zoo FunASR has open-sourced a large number of pre-trained models on industrial data. You are free to use, copy, modify, and share FunASR models under the [Model License Agreement](./MODEL_LICENSE). Below are some representative models, for more models please refer to the [Model Zoo](). -(Note: 猸� represents the ModelScope model zoo link, 馃 represents the Huggingface model zoo link) +(Note: 猸� represents the ModelScope model zoo, 馃 represents the Huggingface model zoo, 馃崁 represents the OpenAI model zoo) -| Model Name | Task Details | Training Data | Parameters | -|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------:|:--------------------------------:|:----------:| -| paraformer-zh <br> ([猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [馃](https://huggingface.co/funasr/paraformer-tp) ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | -| <nobr>paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> | speech recognition, streaming | 60000 hours, Mandarin | 220M | -| paraformer-en <br> ( [猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [馃](https://huggingface.co/funasr/paraformer-en) ) | speech recognition, with timestamps, non-streaming | 50000 hours, English | 220M | -| conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃](https://huggingface.co/funasr/conformer-en) ) | speech recognition, non-streaming | 50000 hours, English | 220M | -| ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) ) | punctuation restoration | 100M, Mandarin and English | 1.1G | -| fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃](https://huggingface.co/funasr/fsmn-vad) ) | voice activity detection | 5000 hours, Mandarin and English | 0.4M | -| fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃](https://huggingface.co/funasr/fa-zh) ) | timestamp prediction | 5000 hours, Mandarin | 38M | -| cam++ <br> ( [猸怾(https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [馃](https://huggingface.co/funasr/campplus) ) | speaker verification/diarization | 5000 hours | 7.2M | -| whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary) [馃]() ) | speech recognition, with timestamps, non-streaming | multilingual | 1G | +| Model Name | Task Details | Training Data | Parameters | +|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------:|:--------------------------------:|:----------:| +| paraformer-zh <br> ([猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [馃](https://huggingface.co/funasr/paraformer-tp) ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | +| <nobr>paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> | speech recognition, streaming | 60000 hours, Mandarin | 220M | +| paraformer-en <br> ( [猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [馃](https://huggingface.co/funasr/paraformer-en) ) | speech recognition, without timestamps, non-streaming | 50000 hours, English | 220M | +| conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃](https://huggingface.co/funasr/conformer-en) ) | speech recognition, non-streaming | 50000 hours, English | 220M | +| ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) ) | punctuation restoration | 100M, Mandarin and English | 1.1G | +| fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃](https://huggingface.co/funasr/fsmn-vad) ) | voice activity detection | 5000 hours, Mandarin and English | 0.4M | +| fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃](https://huggingface.co/funasr/fa-zh) ) | timestamp prediction | 5000 hours, Mandarin | 38M | +| cam++ <br> ( [猸怾(https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [馃](https://huggingface.co/funasr/campplus) ) | speaker verification/diarization | 5000 hours | 7.2M | +| Whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary) [馃崁](https://github.com/openai/whisper) ) | speech recognition, with timestamps, non-streaming | multilingual | 1.5G | +| Whisper-large-v3 <br> ([猸怾(https://www.modelscope.cn/models/iic/Whisper-large-v3/summary) [馃崁](https://github.com/openai/whisper) ) | speech recognition, with timestamps, non-streaming | multilingual | 1.5G | +| Qwen-Audio <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo.py) [馃](https://huggingface.co/Qwen/Qwen-Audio) ) | audio-text multimodal models (pretraining) | multilingual | 8B | +| Qwen-Audio-Chat <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo_chat.py) [馃](https://huggingface.co/Qwen/Qwen-Audio-Chat) ) | audio-text multimodal models (chat) | multilingual | 8B | @@ -205,7 +210,37 @@ More examples ref to [docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining) -[//]: # (FunASR supports inference and fine-tuning of models trained on industrial datasets of tens of thousands of hours. For more details, please refer to ([modelscope_egs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)). It also supports training and fine-tuning of models on academic standard datasets. For more details, please refer to([egs](https://alibaba-damo-academy.github.io/FunASR/en/academic_recipe/asr_recipe.html)). The models include speech recognition (ASR), speech activity detection (VAD), punctuation recovery, language model, speaker verification, speaker separation, and multi-party conversation speech recognition. For a detailed list of models, please refer to the [Model Zoo](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md):) + +## Export ONNX + +### Command-line usage +```shell +funasr-export ++model=paraformer ++quantize=false ++device=cpu +``` + +### Python +```python +from funasr import AutoModel + +model = AutoModel(model="paraformer", device="cpu") + +res = model.export(quantize=False) +``` + +### Text ONNX +```python +# pip3 install -U funasr-onnx +from funasr_onnx import Paraformer +model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" +model = Paraformer(model_dir, batch_size=1, quantize=True) + +wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav'] + +result = model(wav_path) +print(result) +``` + +More examples ref to [demo](runtime/python/onnxruntime) ## Deployment Service FunASR supports deploying pre-trained or further fine-tuned models for service. Currently, it supports the following types of service deployment: @@ -224,9 +259,9 @@ You can also scan the following DingTalk group or WeChat group QR code to join the community group for communication and discussion. -|DingTalk group | WeChat group | -|:---:|:-----------------------------------------------------:| -|<div align="left"><img src="docs/images/dingding.jpg" width="250"/> | <img src="docs/images/wechat.png" width="215"/></div> | +| DingTalk group | WeChat group | +|:-------------------------------------------------------------------:|:-----------------------------------------------------:| +| <div align="left"><img src="docs/images/dingding.png" width="250"/> | <img src="docs/images/wechat.png" width="215"/></div> | ## Contributors -- Gitblit v1.9.1