Instructions to use Gramscii-IT/dots.mocr-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 Gramscii-IT/dots.mocr-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 Gramscii-IT/dots.mocr-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf Gramscii-IT/dots.mocr-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Gramscii-IT/dots.mocr-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf Gramscii-IT/dots.mocr-GGUF:F16

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 Gramscii-IT/dots.mocr-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf Gramscii-IT/dots.mocr-GGUF:F16

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 Gramscii-IT/dots.mocr-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Gramscii-IT/dots.mocr-GGUF:F16

Use Docker

docker model run hf.co/Gramscii-IT/dots.mocr-GGUF:F16

LM Studio
Jan

vLLM

How to use Gramscii-IT/dots.mocr-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Gramscii-IT/dots.mocr-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": "Gramscii-IT/dots.mocr-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/Gramscii-IT/dots.mocr-GGUF:F16

Ollama
How to use Gramscii-IT/dots.mocr-GGUF with Ollama:
```
ollama run hf.co/Gramscii-IT/dots.mocr-GGUF:F16
```
Unsloth Desktop
Docker Model Runner
How to use Gramscii-IT/dots.mocr-GGUF with Docker Model Runner:
```
docker model run hf.co/Gramscii-IT/dots.mocr-GGUF:F16
```

Lemonade

How to use Gramscii-IT/dots.mocr-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Gramscii-IT/dots.mocr-GGUF:F16

Run and chat with the model

lemonade run user.dots.mocr-GGUF-F16

List all available models

lemonade list

Atomic Chat

dots.mocr GGUF

GGUF conversion of dots-studio/dots.mocr for llama.cpp. Built with dots.mocr.

Nothing about the model was changed: these are the published weights in a different container, plus quantized variants of that same conversion.

Provenance

Source: dots-studio/dots.mocr, revision e539fbb52280393adc081b289ec597430a0f9031, every file verified by sha256 before conversion.
Converter: llama.cpp convert_hf_to_gguf.py (master, 2026-08-21, commit 1719747), whose DotsOCRForCausalLM support landed with PR #17575. The language model converts as a qwen2-architecture GGUF; the vision tower converts separately as a dots_ocr multimodal projector.
Quantization: llama-quantize Q8_0 from the f16 conversion, in the same llama.cpp build.

Files

file	bytes	sha256
`dots.mocr-f16.gguf`	3560414496	`3bb7e8255bb79affad42cb1b20c4ed8807b792bbe19d880ef78852aca1546350`
`dots.mocr-q8_0.gguf`	1894530336	`3c23dd35a3cdf9e1328f3a22066fa9b4a16815e5ce58a55bcc015d7944445a18`
`mmproj-dots.mocr-f16.gguf`	2524490688	`2d3505b44db99c4ab7301771aaf1f2db1866e7da061b999ba4fa086a8be36e76`
`mmproj-dots.mocr-q8_0.gguf`	1344068544	`bbdf3b8c0e7f81af6ba5c646dc1fefd40f80fffde0d2fdc8ca1209a2d82b76af`

Usage

llama-server -m dots.mocr-q8_0.gguf --mmproj mmproj-dots.mocr-q8_0.gguf \
  --host 127.0.0.1 --port 8080

Requires a llama.cpp build that ships PROJECTOR_TYPE_DOTS_OCR (b8731 or later). If you are serving with vLLM or Transformers, use the original repository: these files buy you nothing there.

License and attribution

The model weights remain under the dots.mocr License Agreement, unchanged from the model these files were converted from; a copy travels with this repository, as the agreement requires, together with the upstream NOTICE. Built with dots.mocr.

Downloads last month: -

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

8-bit

16-bit

Model tree for Gramscii-IT/dots.mocr-GGUF

Base model

dots-studio/dots.mocr

Quantized

(15)

this model