Find agent skills by outcome

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中文&nbsp ｜ &nbspEnglish&nbsp&nbsp ｜ &nbsp日本語&nbsp ｜ &nbsp한국어&nbsp

Qwen-VL-Chat Tutorial

Qwen-VL-Chat is a generalist multimodal large-scale language model, and it can perform a wide range of vision-language tasks. In this tutorial, we will give some concise examples to demonstrate the ca...

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中文&nbsp ｜ &nbspEnglish&nbsp&nbsp ｜ &nbsp日本語&nbsp｜ &nbsp한국어&nbsp

Untitled Skill

中文&nbsp ｜ &nbsp English&nbsp ｜ &nbsp日本語&nbsp

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中文&nbsp ｜ &nbspEnglish&nbsp&nbsp ｜ &nbsp日本語&nbsp｜ &nbsp한국어&nbsp

FAQ

4.31.0 버전을 사용하는 것을 선호합니다.

FAQ

建议使用4.31.0。

FAQ

4.31.0 is preferred.

FAQ

4.31.0 が望ましいです。

pycache

*.so

qwen web demo

docker build -t qwen-vl-chat:webdemo --platform linux/amd64 -f Dockerfile.qwendemo .

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exclude: ^internvlchatllava/

repos:

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[flake8]

ignore = E501, F403, C901, W504, W605, E251, E122, E126, E127, E722, W503, E128, E741, E731, E701

🛠️ Installation

- Clone this repository:

Byte-compiled / optimized / DLL files

pycache/

CogVLM-SFT-311K：CogVLM SFT 中的双语视觉指令数据集

CogVLM-SFT-311K 是我们在训练 CogVLM v1.0 最初版本时使用的主要对齐语料库。此数据集的构建过程如下：

CogVLM-SFT-311K: Bilingual Visual Instruction Data in CogVLM SFT

CogVLM-SFT-311K is the primary aligned corpus used in the initial training of CogVLM v1.0. The process of constructing this dataset is as follows:

CogVLM & CogAgent

📗 README in English

CogVLM & CogAgent

📗 中文版README

SATHOME=~/.satmodels

LOCALWORLDSIZE=8

.hypothesis/

pycache

Configuration for Cog ⚙️

build: