SkyVision.cpp
Collection
8 items • Updated • 1
How to use SkyContact/VideoChat3-4B-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf SkyContact/VideoChat3-4B-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf SkyContact/VideoChat3-4B-GGUF:Q6_K
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SkyContact/VideoChat3-4B-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf SkyContact/VideoChat3-4B-GGUF:Q6_K
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf SkyContact/VideoChat3-4B-GGUF:Q6_K # Run inference directly in the terminal: ./llama-cli -hf SkyContact/VideoChat3-4B-GGUF:Q6_K
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf SkyContact/VideoChat3-4B-GGUF:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf SkyContact/VideoChat3-4B-GGUF:Q6_K
docker model run hf.co/SkyContact/VideoChat3-4B-GGUF:Q6_K
How to use SkyContact/VideoChat3-4B-GGUF with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SkyContact/VideoChat3-4B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "SkyContact/VideoChat3-4B-GGUF",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/SkyContact/VideoChat3-4B-GGUF:Q6_K
How to use SkyContact/VideoChat3-4B-GGUF with Ollama:
ollama run hf.co/SkyContact/VideoChat3-4B-GGUF:Q6_K
How to use SkyContact/VideoChat3-4B-GGUF with Docker Model Runner:
docker model run hf.co/SkyContact/VideoChat3-4B-GGUF:Q6_K
How to use SkyContact/VideoChat3-4B-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SkyContact/VideoChat3-4B-GGUF:Q6_K
lemonade run user.VideoChat3-4B-GGUF-Q6_K
lemonade list
MCG-NJU/VideoChat3-4B 的 GGUF 量化版本, 配套推理引擎 SkyVision.cpp。
仅供 SkyVision.cpp 使用。 GGUF 里
general.architecture = videochat3, 是自研的 Qwen3 + VideoChat3 ViT 结构,llama.cpp / ollama / LM Studio 等通用 GGUF 运行时无法加载本仓库文件。 本仓库与通用 GGUF 生态不兼容,请勿据此判断"能不能跑"。
| 文件 | 量化 | 大小 | 说明 |
|---|---|---|---|
videochat3-4b-q6_k.gguf |
Q6_K | ~3.9 GB | 单文件自包含:Qwen3 文本解码器 + 27 层 ViT + multimodal projector |
单个 GGUF 装下全部张量,不需要额外的 vision 文件(这一点与 moondream3.1 不同)。 ViT 与 multimodal projector 保持 F16,学习式位置编码表保持 F32(由宿主端做双三次插值)。
模型结构:
n_ctx = 8192SkyVision.cpp(vqa-cli),CUDA 与 CPU 后端均可。tokenizer.json
(--tokenizer <检查点目录>)。vqa-cli --video <file> --fps 2 --max-frames 32,走 ffmpeg 管道解码,需要 PATH 上有 ffmpeg。(H/28)×(W/28),默认 n_ctx 8192 大致只装得下 6 MP 以内的图片;
更大的图请先缩小,否则会报 context overflow。SkyVision.cppApache-2.0,继承自基座模型。
6-bit
Base model
MCG-NJU/VideoChat3-4B