Instructions to use Hansda/ScreenVLM-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Hansda/ScreenVLM-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Hansda/ScreenVLM-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Hansda/ScreenVLM-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Hansda/ScreenVLM-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Hansda/ScreenVLM-GGUF:F16
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Hansda/ScreenVLM-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf Hansda/ScreenVLM-GGUF:F16
Use Docker
docker model run hf.co/Hansda/ScreenVLM-GGUF:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use Hansda/ScreenVLM-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Hansda/ScreenVLM-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Hansda/ScreenVLM-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Hansda/ScreenVLM-GGUF:F16
- Ollama
How to use Hansda/ScreenVLM-GGUF with Ollama:
ollama run hf.co/Hansda/ScreenVLM-GGUF:F16
- Unsloth Desktop
- Docker Model Runner
How to use Hansda/ScreenVLM-GGUF with Docker Model Runner:
docker model run hf.co/Hansda/ScreenVLM-GGUF:F16
- Lemonade
How to use Hansda/ScreenVLM-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Hansda/ScreenVLM-GGUF:F16
Run and chat with the model
lemonade run user.ScreenVLM-GGUF-F16
List all available models
lemonade list
- Atomic Chat
Download runtime-info.json from Hansda/ScreenVLM-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.46 kB
-
https://huggingface.co/Hansda/ScreenVLM-GGUF/resolve/main/runtime-info.json
- Command line
-
hf download hf://Hansda/ScreenVLM-GGUF/runtime-info.json
-
curl -L -o runtime-info.json https://huggingface.co/Hansda/ScreenVLM-GGUF/resolve/main/runtime-info.json
1.46 kB
| { | |
| "repository": "https://github.com/ggml-org/llama.cpp", | |
| "revision": "0ec4027a2a0183de87c007069adddc06e665f7de", | |
| "source_tree_clean": true, | |
| "build": { | |
| "type": "Release", | |
| "cuda": true, | |
| "cuda_toolkit": "13.0.88", | |
| "cuda_arch": "120a", | |
| "native_cpu": true, | |
| "build_parallelism": 4 | |
| }, | |
| "python": { | |
| "torch": "2.14.0+cu130", | |
| "transformers": "5.17.0", | |
| "huggingface_hub": "1.32.0", | |
| "safetensors": "0.8.0", | |
| "tokenizers": "0.23.2", | |
| "numpy": "2.5.3", | |
| "Pillow": "12.3.0", | |
| "gguf": "0.19.0", | |
| "sentencepiece": "0.2.2" | |
| }, | |
| "tools": { | |
| "llama-server": { | |
| "sha256": "12255637a664054701e296e3b9a0cdfeda4d62380c9c7af598f4408e9f6c21bd", | |
| "bytes": 17888 | |
| }, | |
| "llama-quantize": { | |
| "sha256": "3048c984ce69c78e4898f94fca85949384806114a02028ef03e175c1ced54e4d", | |
| "bytes": 17888 | |
| }, | |
| "llama-cli": { | |
| "sha256": "26ade31d637ae6ac69d398a38dd021d5fc5a9a23aced091f8e4a1d21e4d3358a", | |
| "bytes": 1474576 | |
| }, | |
| "llama-mtmd-cli": { | |
| "sha256": "2d607d2a8d5a42d949340789d3bdf82295aae3010621beec7864842e77662bce", | |
| "bytes": 106520 | |
| } | |
| }, | |
| "model_notes": { | |
| "special_output_flag": "--special required to retain location prefix control token", | |
| "processor": "IDEFICS3: longest edge 2048, 512px tiles plus overview, 4x pixel shuffle, mean/std 0.5, Lanczos. Do not add Qwen-specific image-token limits.", | |
| "tested_context": 4096, | |
| "tested_threads": 4 | |
| } | |
| } | |