From 31bf3a88a09f6e7c895224f4dc75e8f2c138d5c8 Mon Sep 17 00:00:00 2001
From: 雾聪 <wucong.lyb@alibaba-inc.com>
Date: 星期一, 01 七月 2024 20:43:06 +0800
Subject: [PATCH] update funasr-runtime-sdk-gpu-0.1.1

---
 README.md |   28 +++++++++++++++++++---------
 1 files changed, 19 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index c27ff7c..0cdbf64 100644
--- a/README.md
+++ b/README.md
@@ -29,6 +29,8 @@
 
 <a name="whats-new"></a>
 ## What's new:
+- 2024/07/01: Offline File Transcription Service GPU 1.1 released, optimize BladeDISC model compatibility issues; ref to ([docs](runtime/readme.md))
+- 2024/06/27: Offline File Transcription Service GPU 1.0 released, supporting dynamic batch processing and multi-threading concurrency. In the long audio test set, the single-thread RTF is 0.0076, and multi-threads' speedup is 1200+ (compared to 330+ on CPU); ref to ([docs](runtime/readme.md))
 - 2024/05/15锛歟motion recognition models are new supported. [emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)锛孾emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary)锛孾emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary). currently supports the following categories: 0: angry 1: happy 2: neutral 3: sad 4: unknown.
 - 2024/05/15: Offline File Transcription Service 4.5, Offline File Transcription Service of English 1.6锛孯eal-time Transcription Service 1.10 released锛宎dapting to FunASR 1.0 model structure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).
@@ -60,18 +62,26 @@
 <a name="Installation"></a>
 ## Installation
 
+- Requirements
+```text
+python>=3.8
+torch>=1.13
+torchaudio
+```
+
+- Install for pypi
 ```shell
 pip3 install -U funasr
 ```
-Or install from source code
+- Or install from source code
 ``` sh
 git clone https://github.com/alibaba/FunASR.git && cd FunASR
 pip3 install -e ./
 ```
-Install modelscope for the pretrained models (Optional)
+- Install modelscope or huggingface_hub for the pretrained models (Optional)
 
 ```shell
-pip3 install -U modelscope
+pip3 install -U modelscope huggingface_hub
 ```
 
 ## Model Zoo
@@ -86,15 +96,15 @@
 | <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    | 
+|                               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    |    290M    | 
 |                                   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           |    1550 M    |
-|                                            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           |    1550 M    |
-|                                               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  |
-|                              emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                               |              speech emotion recongintion              |           40000 hours            |  300M  |
+|                                 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           |   1550 M   |
+|                                            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           |   1550 M   |
+|                                               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     |
+|                              emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                               |              speech emotion recongintion              |           40000 hours            |    300M    |
 
 
 

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