Instructions to use gabriellarson/Nanonets-OCR-s-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 gabriellarson/Nanonets-OCR-s-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 gabriellarson/Nanonets-OCR-s-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf gabriellarson/Nanonets-OCR-s-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf gabriellarson/Nanonets-OCR-s-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf gabriellarson/Nanonets-OCR-s-GGUF:BF16

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 gabriellarson/Nanonets-OCR-s-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf gabriellarson/Nanonets-OCR-s-GGUF:BF16

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 gabriellarson/Nanonets-OCR-s-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gabriellarson/Nanonets-OCR-s-GGUF:BF16

Use Docker

docker model run hf.co/gabriellarson/Nanonets-OCR-s-GGUF:BF16

LM Studio
Jan

vLLM

How to use gabriellarson/Nanonets-OCR-s-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gabriellarson/Nanonets-OCR-s-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": "gabriellarson/Nanonets-OCR-s-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/gabriellarson/Nanonets-OCR-s-GGUF:BF16

Ollama
How to use gabriellarson/Nanonets-OCR-s-GGUF with Ollama:
```
ollama run hf.co/gabriellarson/Nanonets-OCR-s-GGUF:BF16
```

Unsloth Studio

How to use gabriellarson/Nanonets-OCR-s-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 gabriellarson/Nanonets-OCR-s-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 gabriellarson/Nanonets-OCR-s-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for gabriellarson/Nanonets-OCR-s-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use gabriellarson/Nanonets-OCR-s-GGUF with Docker Model Runner:
```
docker model run hf.co/gabriellarson/Nanonets-OCR-s-GGUF:BF16
```

Lemonade

How to use gabriellarson/Nanonets-OCR-s-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gabriellarson/Nanonets-OCR-s-GGUF:BF16

Run and chat with the model

lemonade run user.Nanonets-OCR-s-GGUF-BF16

List all available models

lemonade list

How to run with mmproj

by ShulgaSA - opened Jun 13, 2025

Discussion

ShulgaSA

Jun 13, 2025

Can someone provide some sample code on how to run this model locally via llama_cpp_python?

I don't understand how to pick up the mmproj file along with the gguf ..

gabriellarson

Owner Jun 13, 2025

I havent used llama_cpp_python but it looks like you use "clip_model_path"

example taken from: https://github.com/abetlen/llama-cpp-python/blob/b1d23df0bbd327b774083b5cf88e67ca0dd52b92/docs/server.md
{
"model": "models/ggml_llava-v1.5-7b/ggml-model-q4_k.gguf",
"model_alias": "gpt-4-vision-preview",
"chat_format": "llava-1-5",
"clip_model_path": "models/ggml_llava-v1.5-7b/mmproj-model-f16.gguf",
"n_gpu_layers": -1,
"offload_kqv": true,
"n_threads": 12,
"n_batch": 512,
"n_ctx": 2048
}

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