From 1fadb21eb61dc0e4df987eaf0f9c59bdacec6ca4 Mon Sep 17 00:00:00 2001 From: 游雁 <zhifu.gzf@alibaba-inc.com> Date: 星期五, 05 五月 2023 18:49:33 +0800 Subject: [PATCH] docs --- egs_modelscope/punctuation/TEMPLATE/README.md | 6 +++--- 1 files changed, 3 insertions(+), 3 deletions(-) diff --git a/egs_modelscope/punctuation/TEMPLATE/README.md b/egs_modelscope/punctuation/TEMPLATE/README.md index dfbe044..08814ea 100644 --- a/egs_modelscope/punctuation/TEMPLATE/README.md +++ b/egs_modelscope/punctuation/TEMPLATE/README.md @@ -1,7 +1,7 @@ # Punctuation Restoration > **Note**: -> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetune. Here we take the model of the punctuation model of CT-Transformer as example to demonstrate the usage. +> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/model_zoo/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetune. Here we take the model of the punctuation model of CT-Transformer as example to demonstrate the usage. ## Inference @@ -55,7 +55,7 @@ ### API-reference #### Define pipeline - `task`: `Tasks.punctuation` -- `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk +- `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/model_zoo/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk - `ngpu`: `1` (Default), decoding on GPU. If ngpu=0, decoding on CPU - `output_dir`: `None` (Default), the output path of results if set - `model_revision`: `None` (Default), setting the model version @@ -71,7 +71,7 @@ FunASR also offer recipes [egs_modelscope/punctuation/TEMPLATE/infer.sh](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs_modelscope/punctuation/TEMPLATE/infer.sh) to decode with multi-thread CPUs, or multi GPUs. It is an offline recipe and only support offline model. #### Settings of `infer.sh` -- `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk +- `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/model_zoo/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk - `data_dir`: the dataset dir needs to include `punc.txt` - `output_dir`: output dir of the recognition results - `gpu_inference`: `true` (Default), whether to perform gpu decoding, set false for CPU inference -- Gitblit v1.9.1