python/FunASR-XL.git

			@@ -2,8 +2,6 @@

			[FunASR](https://github.com/alibaba-damo-academy/FunASR) hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model released on ModelScope, researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun！

			### Introduction
			- Model comes from [speech_paraformer](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary).

			### Steps:
			1. Export the model.
			@@ -22,10 +20,24 @@


			2. Install the `funasr_torch`.

			install from pip
			```shell
			pip install funasr_torch -i https://pypi.Python.org/simple
			```
			pip install -U funasr_torch
			# For the users in China, you could install with the command:
			# pip install -U funasr_torch -i https://mirror.sjtu.edu.cn/pypi/web/simple

			```
			or install from source code

			```shell
			git clone https://github.com/alibaba/FunASR.git && cd FunASR
			cd funasr/runtime/python/libtorch
			pip install -e ./
			# For the users in China, you could install with the command:
			# pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple

			```

			3. Run the demo.
			- Model_dir: the model path, which contains `model.torchscripts`, `config.yaml`, `am.mvn`.
			@@ -44,6 +56,10 @@
			print(result)
			```

			## Performance benchmark

			Please ref to [benchmark](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_libtorch.md)

			## Speed

			Environment：Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz