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

File size: 496 Bytes

2bd2482

# Use an official Python base image
FROM python:3.10-slim

# Set working directory
WORKDIR /app

# Install system dependencies (if needed)
RUN apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*

# Copy your project files
COPY . /app

# Install Python dependencies
RUN pip install --upgrade pip
RUN pip install -r requirements.txt

# Expose the port your FastAPI app runs on
EXPOSE 7860

# Run the FastAPI app
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]