Instructions to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/zai-org_GLM-4.6V-Flash-GGUF", filename="mmproj-zai-org_GLM-4.6V-Flash-bf16.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/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
- Ollama
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with Ollama:
ollama run hf.co/bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
- Unsloth Studio new
How to use bartowski/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-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/zai-org_GLM-4.6V-Flash-GGUF to start chatting
- Pi new
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
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": "bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
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 bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
- Lemonade
How to use bartowski/zai-org_GLM-4.6V-Flash-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/zai-org_GLM-4.6V-Flash-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.zai-org_GLM-4.6V-Flash-GGUF-Q4_K_M
List all available models
lemonade list
mmproj file?
will there be mmproj files with these GLM 4.6V releases? Thanks
I'll try it again but no it didn't manage to generate for some reason
Vision model without vision support is like a pirate without parrot.
Yeah I was surprised to see it convert at all but then not having vision, I assume there was something complicated, I'll dig around if I remember later
this model is supported text only now
details https://github.com/ggml-org/llama.cpp/pull/14823
pull request for vision https://github.com/ggml-org/llama.cpp/pull/16600
Yeah I was surprised to see it convert at all but then not having vision, I assume there was something complicated, I'll dig around if I remember later
Hey thanks for trying. Hopefully they fulfill the pull request for vision.
Thanks for jumping on this so fast! I take it that you'll be doing the 4.6V large model, too? You're the best!
Also, anyone else having trouble getting this to load with mmproj files? I can load the bare model without the mmproj files in TextGenWebUI/Oobabooga. But I've tried the bartowski BF16 mmproj as well as the ggml Q8 mmproj, and neither would allow the model to load.
???
Also, anyone else having trouble getting this to load with mmproj files? I can load the bare model without the mmproj files in TextGenWebUI/Oobabooga. But I've tried the bartowski BF16 mmproj as well as the ggml Q8 mmproj, and neither would allow the model to load.
???
Your LLM client needs at least this backend build: llama.cpp b7429 https://github.com/ggml-org/llama.cpp/releases/tag/b7429
I don't know if you can manually update llama.cpp in Oobabooga; otherwise, you'll need to wait until it's updated.
Also, anyone else having trouble getting this to load with mmproj files? I can load the bare model without the mmproj files in TextGenWebUI/Oobabooga. But I've tried the bartowski BF16 mmproj as well as the ggml Q8 mmproj, and neither would allow the model to load.
???
Your LLM client needs at least this backend build: llama.cpp b7429 https://github.com/ggml-org/llama.cpp/releases/tag/b7429
I don't know if you can manually update llama.cpp in Oobabooga; otherwise, you'll need to wait until it's updated.
Thanks! The latest Oobabooga was updated two days ago. So it didn't include these most recent changes.
So I just went to the link you posted... and then I downloaded 'llama-b7429-bin-win-cuda-12.4-x64.zip' and 'cudart-llama-bin-win-cuda-12.4-x64.zip' ... then I extracted their contents and copied all files to the Oobabooga llama.cpp bin folder which manually updates Oobabooga. And yes, the model instantly loaded with the mmproj file and vision capability π
Thanks for your help!
if anyone was using the bf16 mmproj there was apparently a bug with it, resolved on master here:
https://github.com/ggml-org/llama.cpp/pull/18124
pushed the new mmproj files here and to GLM-4.6V
Yeah I learned that the hard way. The BF16 mmproj wouldn't load for me. But I already had their Q8 mmproj, and I also grabbed your F16 mmproj just to see if there was a difference. I think yours was a little "smarter," but there's was a little more human-like. Idk, maybe it's just me tho? Anyway, it works! Thanks again for being so on top of this. It's a great model.