Find agent skills by outcome

FAQ

4.31.0 が望ましいです。

FAQ

建议使用4.31.0。

FAQ

4.31.0 버전을 사용하는 것을 선호합니다.

FAQ

4.31.0 is preferred.

qwen web demo

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

pycache

*.so

Untitled Skill

🛠️ Installation

- Clone this repository:

exclude: ^internvlchatllava/

repos:

[flake8]

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

Byte-compiled / optimized / DLL files

pycache/

Untitled Skill

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:

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

* text=auto

🌋 LLaVA: Large Language and Vision Assistant

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

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

.git

root = true

[*]

Python

pycache