Instructions to use kucingcoder/Pegon-AI-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use kucingcoder/Pegon-AI-VL with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="kucingcoder/Pegon-AI-VL", filename="Qwen3-VL-2B-Instruct.F16-mmproj.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kucingcoder/Pegon-AI-VL with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kucingcoder/Pegon-AI-VL:F16 # Run inference directly in the terminal: llama-cli -hf kucingcoder/Pegon-AI-VL:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kucingcoder/Pegon-AI-VL:F16 # Run inference directly in the terminal: llama-cli -hf kucingcoder/Pegon-AI-VL:F16
Use pre-built binary
# 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 kucingcoder/Pegon-AI-VL:F16 # Run inference directly in the terminal: ./llama-cli -hf kucingcoder/Pegon-AI-VL:F16
Build from source code
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 kucingcoder/Pegon-AI-VL:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf kucingcoder/Pegon-AI-VL:F16
Use Docker
docker model run hf.co/kucingcoder/Pegon-AI-VL:F16
- LM Studio
- Jan
- Ollama
How to use kucingcoder/Pegon-AI-VL with Ollama:
ollama run hf.co/kucingcoder/Pegon-AI-VL:F16
- Unsloth Studio
How to use kucingcoder/Pegon-AI-VL with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kucingcoder/Pegon-AI-VL to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kucingcoder/Pegon-AI-VL to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kucingcoder/Pegon-AI-VL to start chatting
- Pi
How to use kucingcoder/Pegon-AI-VL with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf kucingcoder/Pegon-AI-VL:F16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "kucingcoder/Pegon-AI-VL:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use kucingcoder/Pegon-AI-VL with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf kucingcoder/Pegon-AI-VL:F16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default kucingcoder/Pegon-AI-VL:F16
Run Hermes
hermes
- Docker Model Runner
How to use kucingcoder/Pegon-AI-VL with Docker Model Runner:
docker model run hf.co/kucingcoder/Pegon-AI-VL:F16
- Lemonade
How to use kucingcoder/Pegon-AI-VL with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kucingcoder/Pegon-AI-VL:F16
Run and chat with the model
lemonade run user.Pegon-AI-VL-F16
List all available models
lemonade list
| { | |
| "architectures": [ | |
| "Qwen3VLForConditionalGeneration" | |
| ], | |
| "bos_token_id": null, | |
| "torch_dtype": "float16", | |
| "eos_token_id": 151645, | |
| "image_token_id": 151655, | |
| "model_name": "unsloth/Qwen3-VL-2B-Instruct", | |
| "model_type": "qwen3_vl", | |
| "pad_token_id": 151654, | |
| "text_config": { | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "torch_dtype": "float16", | |
| "eos_token_id": 151645, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6144, | |
| "max_position_embeddings": 262144, | |
| "model_type": "qwen3_vl_text", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": null, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "mrope_interleaved": true, | |
| "mrope_section": [ | |
| 24, | |
| 20, | |
| 20 | |
| ], | |
| "rope_theta": 5000000, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "use_cache": true, | |
| "vocab_size": 151936 | |
| }, | |
| "tie_word_embeddings": true, | |
| "unsloth_fixed": true, | |
| "unsloth_version": "2026.6.1", | |
| "use_cache": false, | |
| "video_token_id": 151656, | |
| "vision_config": { | |
| "deepstack_visual_indexes": [ | |
| 5, | |
| 11, | |
| 17 | |
| ], | |
| "depth": 24, | |
| "torch_dtype": "float16", | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 1024, | |
| "in_channels": 3, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "model_type": "qwen3_vl", | |
| "num_heads": 16, | |
| "num_position_embeddings": 2304, | |
| "out_hidden_size": 2048, | |
| "patch_size": 16, | |
| "spatial_merge_size": 2, | |
| "temporal_patch_size": 2 | |
| }, | |
| "vision_end_token_id": 151653, | |
| "vision_start_token_id": 151652 | |
| } |