Instructions to use noctrex/Chandra-OCR-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use noctrex/Chandra-OCR-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="noctrex/Chandra-OCR-GGUF", filename="Chandra-OCR-BF16.gguf", )
llm.create_chat_completion( messages = "\"cats.jpg\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use noctrex/Chandra-OCR-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf noctrex/Chandra-OCR-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf noctrex/Chandra-OCR-GGUF:Q4_K_M
Use Docker
docker model run hf.co/noctrex/Chandra-OCR-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use noctrex/Chandra-OCR-GGUF with Ollama:
ollama run hf.co/noctrex/Chandra-OCR-GGUF:Q4_K_M
- Unsloth Studio new
How to use noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for noctrex/Chandra-OCR-GGUF to start chatting
- Pi new
How to use noctrex/Chandra-OCR-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf noctrex/Chandra-OCR-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": "noctrex/Chandra-OCR-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-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 noctrex/Chandra-OCR-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use noctrex/Chandra-OCR-GGUF with Docker Model Runner:
docker model run hf.co/noctrex/Chandra-OCR-GGUF:Q4_K_M
- Lemonade
How to use noctrex/Chandra-OCR-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull noctrex/Chandra-OCR-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Chandra-OCR-GGUF-Q4_K_M
List all available models
lemonade list
Any code demonstration to run the GGUF model?
Would you provide demo to run the model on llama.cpp or vllm?
I thought I can serve it via Ollama. However, Ollama seems doesnt' not suuport it yet.
Yes, ollama does not support it. Yes you can use in the other ones you mentioned.
For example with llamacpp:llama-server --port 9090 --n-gpu-layers 99 --ctx-size 65536 --model Chandra-OCR-Q8_0.gguf --mproj mmproj-F32.gguf
And you can connect to it from you programs, through the endpoint http://localhost:9090/v1
It also runs a small webserver to test it, to try it out with http://localhost:9090
Yes, ollama does not support it. Yes you can use in the other ones you mentioned.
For example with llamacpp:llama-server --port 9090 --n-gpu-layers 99 --ctx-size 65536 --model Chandra-OCR-Q8_0.gguf --mproj mmproj-F32.gguf
And you can connect to it from you programs, through the endpointhttp://localhost:9090/v1
It also runs a small webserver to test it, to try it out withhttp://localhost:9090
Thanks for this.
This worked for me.llama-server --port 9090 --n-gpu-layers 99 --ctx-size 65536 --model Chandra-OCR-Q8_0.gguf --mmproj mmproj-F32.gguf
I have the model running on a VM but when i try to send a request with a prompt and an image it just returns a response with the parameters the model is using and based on my prompt. It seems like it doesn't even considers the image i'm sending. Can anyone provide a valid request with an image and a prompt, because i tried many options?
With what are you running it? I use llama.cpp. As the post above with llama-server. I just paste an image in the Web GUI, and tell it "describe this", and it anwsers. Even without a prompt and just an image, it will anser, as this a OCR model
Thank you! I was trying to send multiple request with batches of images, but i got that working now, and also the GUI is working fine. Now the thing is that i cant replicate the responses i get from the GUI so i receive the same results using a script for sending request. I know there is a lot of internal preprocessing going on when you use the GUI both with the image and the prompt itself, but the responses from the GUI are perfect and i need them to be for my project. Any idea how can i check exactly what parameters and what preprocessing is going on so i can try to replicate them?
Try to send it an image one at time, without a prompt and see what it returns