Instructions to use noctrex/Chandra-OCR-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use noctrex/Chandra-OCR-i1-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 noctrex/Chandra-OCR-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf noctrex/Chandra-OCR-i1-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf noctrex/Chandra-OCR-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf noctrex/Chandra-OCR-i1-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-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf noctrex/Chandra-OCR-i1-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-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf noctrex/Chandra-OCR-i1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/noctrex/Chandra-OCR-i1-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use noctrex/Chandra-OCR-i1-GGUF with Ollama:
```
ollama run hf.co/noctrex/Chandra-OCR-i1-GGUF:Q4_K_M
```

Unsloth Studio

How to use noctrex/Chandra-OCR-i1-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-i1-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-i1-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-i1-GGUF to start chatting

How to use noctrex/Chandra-OCR-i1-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf noctrex/Chandra-OCR-i1-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-i1-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use noctrex/Chandra-OCR-i1-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf noctrex/Chandra-OCR-i1-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "noctrex/Chandra-OCR-i1-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use noctrex/Chandra-OCR-i1-GGUF with Docker Model Runner:
```
docker model run hf.co/noctrex/Chandra-OCR-i1-GGUF:Q4_K_M
```

Lemonade

How to use noctrex/Chandra-OCR-i1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull noctrex/Chandra-OCR-i1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Chandra-OCR-i1-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use noctrex/Chandra-OCR-i1-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf noctrex/Chandra-OCR-i1-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-i1-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

These are quantizations of the model Chandra-OCR

This is the imatrix version. text_en_medium has been used to create it.

Original model: https://huggingface.co/datalab-to/chandra

Download the latest llama.cpp to use them.

Try to use the best quality you can run.
For the mmproj, try to use the F32 version as it will produce the best results. F32 > BF16 > F16

Why no Q8_0/F16/BF16 in here? Because these do not use imatrix, so go and download the normal ones from here: noctrex/Chandra-OCR-GGUF.

Downloads last month: 25

GGUF

Model size

8B params

Architecture

qwen3vl

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

Model tree for noctrex/Chandra-OCR-i1-GGUF

Base model

datalab-to/chandra

Quantized

(12)

this model