General
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text files must be lf for golden file tests to work
* text=auto eol=lf
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General
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Microsoft Open Source Code of Conduct
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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General
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Contributing
Playwright **requires an issue** for every contribution, except for minor documentation updates. We strongly recommend
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General
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How to File a Bug Report That Actually Gets Resolved
Make sure you’re on the latest Playwright release before filing. Check existing GitHub issues to avoid duplicates.
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General
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root = true
[*]
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General
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version: "3.8"
services:
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General
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name: pydml
channels:
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General
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.DS_Store
__pycache__
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General
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<div align="center">
<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
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General
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OPENBLAS_NUM_THREADS = 1
no_proxy = localhost, 127.0.0.1, ::1
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General
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贡献规则
1. 一般来说，作者`@RVC-Boss`将拒绝所有的算法更改，除非它是为了修复某个代码层面的错误或警告
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General
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<div align="center">
<div> </div>
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General
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__pycache__/
.ipynb_checkpoints/
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General
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> Notice: Bark is Suno's open-source text-to-speech+ model. If you are looking for our text-to-music models, please visit us on our [web page](https://suno.ai) and join our community on [Discord](http
[](https://suno.ai/discord)
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General
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Model Card: Bark
This is the official codebase for running the text to audio model, from Suno.ai.
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General
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__pycache__/
suno_bark.egg-info/
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General
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CHANGELOG
* Fix: Update torch.load to use weights_only=True to prevent security w… ([#2451](https://github.com/openai/whisper/pull/2451))
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General
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repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
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General
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__pycache__/
*.py[cod]
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General
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Override jupyter in Github language stats for more accurate estimate of repo code languages
*.ipynb linguist-generated
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General
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Model Card: Whisper
This is the official codebase for running the automatic speech recognition (ASR) models (Whisper models) trained and released by OpenAI.
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General
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Whisper
[[Blog]](https://openai.com/blog/whisper)
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General
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[flake8]
per-file-ignores =
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General
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Qwen-VL-Chat チュートリアル
Qwen-VL-Chat は汎用のマルチモーダル大規模言語モデルであり、幅広い視覚言語タスクを実行できます。このチュートリアルでは、Qwen-VL-Chat の**視覚的質問応答、テキスト理解、図を用いた数学的推論、多視点推論、およびグラウンディング**の機能について、いくつかの簡潔な例を挙げて説明します。Qwen-VL-Chat は、入力画像やプロンプトを変更することで、Qwen-VL-Chat の能力をさらに引き出すことができます。
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