From d188604b9674f7c8d42eb430614beef6f89b6993 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 27 四月 2023 19:26:07 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add
---
egs_modelscope/tp/TEMPLATE/README.md | 10 +++++-----
1 files changed, 5 insertions(+), 5 deletions(-)
diff --git a/egs_modelscope/tp/TEMPLATE/README.md b/egs_modelscope/tp/TEMPLATE/README.md
index f511f58..8d75581 100644
--- a/egs_modelscope/tp/TEMPLATE/README.md
+++ b/egs_modelscope/tp/TEMPLATE/README.md
@@ -1,4 +1,4 @@
-# TIMESTAMP PREDICTION
+# Timestamp Prediction (FA)
## Inference
@@ -59,11 +59,11 @@
```
### Inference with multi-thread CPUs or multi GPUs
-FunASR also offer recipes [egs_modelscope/vad/TEMPLATE/infer.sh](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs_modelscope/vad/TEMPLATE/infer.sh) to decode with multi-thread CPUs, or multi GPUs.
+FunASR also offer recipes [egs_modelscope/tp/TEMPLATE/infer.sh](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs_modelscope/tp/TEMPLATE/infer.sh) to decode with multi-thread CPUs, or multi GPUs.
- Setting parameters in `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
- - `data_dir`: the dataset dir **must** include `wav.scp` and `text.scp`
+ - `data_dir`: the dataset dir **must** include `wav.scp` and `text.txt`
- `output_dir`: output dir of the recognition results
- `batch_size`: `64` (Default), batch size of inference on gpu
- `gpu_inference`: `true` (Default), whether to perform gpu decoding, set false for CPU inference
@@ -78,7 +78,7 @@
--model "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" \
--data_dir "./data/test" \
--output_dir "./results" \
- --batch_size 64 \
+ --batch_size 1 \
--gpu_inference true \
--gpuid_list "0,1"
```
@@ -89,7 +89,7 @@
--data_dir "./data/test" \
--output_dir "./results" \
--gpu_inference false \
- --njob 64
+ --njob 1
```
## Finetune with pipeline
--
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