Instructions to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="glebkudr/Infinity-Parser2-Pro-Q8-GGUF", filename="Infinity-Parser2-Pro-Q8_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
Use Docker
docker model run hf.co/glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with Ollama:
ollama run hf.co/glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
- Unsloth Studio
How to use glebkudr/Infinity-Parser2-Pro-Q8-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 glebkudr/Infinity-Parser2-Pro-Q8-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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for glebkudr/Infinity-Parser2-Pro-Q8-GGUF to start chatting
- Pi
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
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": "glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use glebkudr/Infinity-Parser2-Pro-Q8-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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with Docker Model Runner:
docker model run hf.co/glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
- Lemonade
How to use glebkudr/Infinity-Parser2-Pro-Q8-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0
Run and chat with the model
lemonade run user.Infinity-Parser2-Pro-Q8-GGUF-Q8_0
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0# Run inference directly in the terminal:
llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0Use 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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0# Run inference directly in the terminal:
./llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0Build 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 glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0# Run inference directly in the terminal:
./build/bin/llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0Use Docker
docker model run hf.co/glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0Infinity-Parser2-Pro Q8_0 GGUF
This repository contains a local Q8_0 GGUF conversion of infly/Infinity-Parser2-Pro.
If you are looking for a reliable OCR API use sotaocr.com
Files
| File | Size | SHA256 |
|---|---|---|
Infinity-Parser2-Pro-Q8_0.gguf |
36,903,139,968 bytes | 4effd023d153254d676832df662da2613e0266f973b8208ed01a044b0a82a3fc |
Infinity-Parser2-Pro-mmproj-Q8_0.gguf |
614,194,688 bytes | 2a4007556c20769f1f873fb1e02585988dec62e46822a5295afb3df075185637 |
Infinity-Parser2-Pro-mmproj-bf16.gguf |
902,822,528 bytes | c94c47e850a5cfb59f7baceba397416eea9b8da38e3e76f1dd83271a866b8269 |
Recommended projector
Use Infinity-Parser2-Pro-mmproj-bf16.gguf for document parsing and OCR tasks.
It preserves the upstream BF16 vision projector weights more closely than the
Q8_0 projector while adding only a small amount of storage overhead.
Source
- Source model:
infly/Infinity-Parser2-Pro - Source snapshot commit used for conversion:
1d070df7db5acca0ffa75596229070a047704f89 - Conversion toolchain:
llama.cpp, local build from commit5aa3a6459 - Main model quantization:
Q8_0 - Recommended multimodal projector type:
BF16
The main model was converted with MTP disabled for compatibility with the
current GGUF loader metadata (qwen35moe.block_count=40).
Smoke Test
The converted model and multimodal projector were smoke-tested locally with
llama-cli by loading both GGUF files and running a one-token image prompt.
License
The upstream model card states that infly/Infinity-Parser2-Pro is licensed
under Apache-2.0. This converted GGUF distribution follows the same license.
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Model tree for glebkudr/Infinity-Parser2-Pro-Q8-GGUF
Base model
infly/Infinity-Parser2-Pro
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0# Run inference directly in the terminal: llama-cli -hf glebkudr/Infinity-Parser2-Pro-Q8-GGUF:Q8_0