Instructions to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF", filename="OpenGVLab_InternVL3_5-30B-A3B-IQ2_M.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
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 bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
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 bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/OpenGVLab_InternVL3_5-30B-A3B-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": "bartowski/OpenGVLab_InternVL3_5-30B-A3B-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/bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
- Ollama
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with Ollama:
ollama run hf.co/bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
- Unsloth Studio new
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF 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 bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF 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 bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF to start chatting
- Docker Model Runner
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
- Lemonade
How to use bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/OpenGVLab_InternVL3_5-30B-A3B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.OpenGVLab_InternVL3_5-30B-A3B-GGUF-Q4_K_M
List all available models
lemonade list
Is this the pre-trained or the Instruct version?
Just checking since it's hallucinating a lot.
This is the "final" version, they released 4 varieties of each, seems instruct is not the version you're meant to use (I tried instruct at first but it just kept generating it's EOS token mid sentence)
This model seems to generate a lot and doesn't respond to questions. I installed this model by using the ollama run hf_api_here approach. The model did download and was installed properly, but it appears that in both Open-webui and running this model with VQA tasks via ollama run ... approach caused the model to degenerate and not give a coherent output
llama.cpp seems to run it just fine, but I can't convince it to do any reasoning.
Run it with Ollama, I get non-sense reply.
@bartowski "Here, we also open-source the model weights after different training stages for potential research usage. If you're unsure which version to use, please select the one without any suffix, as it has completed the full training pipeline." You are correct!
The 30b-a3b in this repo is so good at vision tasks, it's become my default vlm. I hope more people learn about it.
They also recently released https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B-Flash with ViCo training. Would be nice if you can gguf it. Thank you.