Instructions to use Navaneeth-14/rag-hackathon-app with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Navaneeth-14/rag-hackathon-app 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 Navaneeth-14/rag-hackathon-app:Q4_K_M # Run inference directly in the terminal: llama cli -hf Navaneeth-14/rag-hackathon-app:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Navaneeth-14/rag-hackathon-app:Q4_K_M # Run inference directly in the terminal: llama cli -hf Navaneeth-14/rag-hackathon-app: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 Navaneeth-14/rag-hackathon-app:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Navaneeth-14/rag-hackathon-app: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 Navaneeth-14/rag-hackathon-app:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Navaneeth-14/rag-hackathon-app:Q4_K_M
Use Docker
docker model run hf.co/Navaneeth-14/rag-hackathon-app:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Navaneeth-14/rag-hackathon-app with Ollama:
ollama run hf.co/Navaneeth-14/rag-hackathon-app:Q4_K_M
- Unsloth Studio
How to use Navaneeth-14/rag-hackathon-app 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 Navaneeth-14/rag-hackathon-app 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 Navaneeth-14/rag-hackathon-app to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Navaneeth-14/rag-hackathon-app to start chatting
- Docker Model Runner
How to use Navaneeth-14/rag-hackathon-app with Docker Model Runner:
docker model run hf.co/Navaneeth-14/rag-hackathon-app:Q4_K_M
- Lemonade
How to use Navaneeth-14/rag-hackathon-app with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Navaneeth-14/rag-hackathon-app:Q4_K_M
Run and chat with the model
lemonade run user.rag-hackathon-app-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Navaneethakrishnan commited on
Commit ·
2bd2482
1
Parent(s): 09281fe
Add Dockerfile for Hugging Face Space
Browse files- Dockerfile +21 -0
- requirements.txt +29 -0
Dockerfile
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# Use an official Python base image
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FROM python:3.10-slim
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# Set working directory
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WORKDIR /app
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# Install system dependencies (if needed)
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RUN apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
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# Copy your project files
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COPY . /app
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# Install Python dependencies
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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# Expose the port your FastAPI app runs on
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EXPOSE 7860
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# Run the FastAPI app
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CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
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requirements.txt
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# Core document processing libraries
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PyMuPDF==1.23.8
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python-docx==0.8.11
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beautifulsoup4==4.12.2
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pandas==2.1.4
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requests==2.31.0
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# OCR and image processing
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pytesseract==0.3.10
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Pillow==10.1.0
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opencv-python==4.8.1.78
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pdf2image==1.16.3
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# Table extraction libraries
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tabula-py==2.8.2
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camelot-py[cv]==0.11.0
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# LangChain for text splitting (using compatible versions)
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langchain>=0.1.0,<0.2.0
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langchain-text-splitters>=0.0.1
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langchain-community>=0.0.20
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# Testing dependencies
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pytest==7.4.3
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pytest-cov==4.1.0
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# Additional utilities
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numpy==1.24.3
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lxml==4.9.3
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