Instructions to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="prithivMLmods/docscopeOCR-7B-050425-exp-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prithivMLmods/docscopeOCR-7B-050425-exp-GGUF", dtype="auto") - llama-cpp-python
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="prithivMLmods/docscopeOCR-7B-050425-exp-GGUF", filename="docscopeOCR-7B-050425-exp.IQ4_XS.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
Use Docker
docker model run hf.co/prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prithivMLmods/docscopeOCR-7B-050425-exp-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": "prithivMLmods/docscopeOCR-7B-050425-exp-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/prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
- SGLang
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "prithivMLmods/docscopeOCR-7B-050425-exp-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/docscopeOCR-7B-050425-exp-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 images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "prithivMLmods/docscopeOCR-7B-050425-exp-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/docscopeOCR-7B-050425-exp-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" } } ] } ] }' - Ollama
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with Ollama:
ollama run hf.co/prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
- Unsloth Studio new
How to use prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for prithivMLmods/docscopeOCR-7B-050425-exp-GGUF to start chatting
- Pi new
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf prithivMLmods/docscopeOCR-7B-050425-exp-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": "prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-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 prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with Docker Model Runner:
docker model run hf.co/prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
- Lemonade
How to use prithivMLmods/docscopeOCR-7B-050425-exp-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull prithivMLmods/docscopeOCR-7B-050425-exp-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.docscopeOCR-7B-050425-exp-GGUF-Q4_K_M
List all available models
lemonade list
docscopeOCR-7B-050425-exp-GGUF
The docscopeOCR-7B-050425-exp model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct, optimized for Document-Level Optical Character Recognition (OCR), long-context vision-language understanding, and accurate image-to-text conversion with mathematical LaTeX formatting. Built on top of the Qwen2.5-VL architecture, this model significantly improves document comprehension, structured data extraction, and visual reasoning across diverse input formats.
Model File
| File Name | Size | Format | Description |
|---|---|---|---|
| docscopeOCR-7B-050425-exp.IQ4_XS.gguf | 4.25 GB | GGUF (IQ4_XS) | Int4 extra-small quantized model |
| docscopeOCR-7B-050425-exp.Q2_K.gguf | 3.02 GB | GGUF (Q2_K) | 2-bit quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_L.gguf | 4.09 GB | GGUF (Q3_K_L) | 3-bit large quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_M.gguf | 3.81 GB | GGUF (Q3_K_M) | 3-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_S.gguf | 3.49 GB | GGUF (Q3_K_S) | 3-bit small quantized model |
| docscopeOCR-7B-050425-exp.Q4_K_M.gguf | 4.68 GB | GGUF (Q4_K_M) | 4-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q5_K_M.gguf | 5.44 GB | GGUF (Q5_K_M) | 5-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q5_K_S.gguf | 5.32 GB | GGUF (Q5_K_S) | 5-bit small quantized model |
| docscopeOCR-7B-050425-exp.Q6_K.gguf | 6.25 GB | GGUF (Q6_K) | 6-bit quantized model |
| docscopeOCR-7B-050425-exp.Q8_0.gguf | 8.1 GB | GGUF (Q8_0) | 8-bit quantized model |
| config.json | 36 B | JSON | Configuration file |
| .gitattributes | 2.25 kB | Text | Git attributes configuration |
Quants Usage
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
- Downloads last month
- 120
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Model tree for prithivMLmods/docscopeOCR-7B-050425-exp-GGUF
Base model
Qwen/Qwen2.5-VL-7B-Instruct