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

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

rag-hackathon-app / requirements.txt

Navaneethakrishnan

Add Dockerfile for Hugging Face Space

2bd2482 about 1 year ago

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	# Core document processing libraries
	PyMuPDF==1.23.8
	python-docx==0.8.11
	beautifulsoup4==4.12.2
	pandas==2.1.4
	requests==2.31.0

	# OCR and image processing
	pytesseract==0.3.10
	Pillow==10.1.0
	opencv-python==4.8.1.78
	pdf2image==1.16.3

	# Table extraction libraries
	tabula-py==2.8.2
	camelot-py[cv]==0.11.0

	# LangChain for text splitting (using compatible versions)
	langchain>=0.1.0,<0.2.0
	langchain-text-splitters>=0.0.1
	langchain-community>=0.0.20

	# Testing dependencies
	pytest==7.4.3
	pytest-cov==4.1.0

	# Additional utilities
	numpy==1.24.3
	lxml==4.9.3