Find agent skills by outcome

FAQ

4.31.0 is preferred.

FAQ

4.31.0 が望ましいです。

qwen web demo

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

pycache

*.so

Untitled Skill

[flake8]

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

Untitled Skill

🛠️ Installation

- Clone this repository:

exclude: ^internvlchatllava/

repos:

Byte-compiled / optimized / DLL files

pycache/

CogVLM & CogAgent

📗 中文版README

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 & CogAgent

📗 README in English

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:

.hypothesis/

pycache

SATHOME=~/.satmodels

LOCALWORLDSIZE=8

Configuration for Cog ⚙️

build:

The .dockerignore file excludes files from the container build process.

.git

🌋 LLaVA: Large Language and Vision Assistant

Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.

Python

pycache

https://git-scm.com/docs/gitattributes

* text=auto

root = true

[*]

Security Policy

We take the security of RAGAS seriously. If you discover a security vulnerability in this project, please report it to us privately. Do not report security vulnerabilities through public GitHub issues...

Development Guide for Ragas Monorepo

This comprehensive guide covers development workflows for the Ragas monorepo, designed for both human developers and AI agents.