Instructions to use uproai/ros-7b-v1-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use uproai/ros-7b-v1-gguf 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 uproai/ros-7b-v1-gguf
# Run inference directly in the terminal:
llama cli -hf uproai/ros-7b-v1-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf uproai/ros-7b-v1-gguf
# Run inference directly in the terminal:
llama cli -hf uproai/ros-7b-v1-gguf

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 uproai/ros-7b-v1-gguf
# Run inference directly in the terminal:
./llama-cli -hf uproai/ros-7b-v1-gguf

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 uproai/ros-7b-v1-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf uproai/ros-7b-v1-gguf

Use Docker

docker model run hf.co/uproai/ros-7b-v1-gguf

LM Studio
Jan

vLLM

How to use uproai/ros-7b-v1-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "uproai/ros-7b-v1-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "uproai/ros-7b-v1-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/uproai/ros-7b-v1-gguf

Ollama
How to use uproai/ros-7b-v1-gguf with Ollama:
```
ollama run hf.co/uproai/ros-7b-v1-gguf
```

Unsloth Studio

How to use uproai/ros-7b-v1-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 uproai/ros-7b-v1-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 uproai/ros-7b-v1-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for uproai/ros-7b-v1-gguf to start chatting

Docker Model Runner
How to use uproai/ros-7b-v1-gguf with Docker Model Runner:
```
docker model run hf.co/uproai/ros-7b-v1-gguf
```

Lemonade

How to use uproai/ros-7b-v1-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull uproai/ros-7b-v1-gguf

Run and chat with the model

lemonade run user.ros-7b-v1-gguf-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

GGUF version of uproai/ros-7b-v1

Usage

Install llama.cpp
Run model locally

!./llama-cpp -m ../ros-7b-v1.gguf -n 300 -p 'Continue this where it left off, follow the pattern:\nAfter a long day of work, Kanye West goes to his Kanye Nest to take his Kanye Rest. He wakes up feeling his Kanye Best. Then he’ll get Kanye Dressed on his Kanye Vest to go on a Kanye Quest. He goes to church and becomes Kanye Blessed, then to a hotel room to be a Kanye Guest. Then to school to take his Kanye Test. He forgot to brush his teeth. Did he run out of Kanye Crest? His neighbor stole it, what a Kanye Pest.\n' -ngl 32

Downloads last month: 15

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

uproai
/

ros-7b-v1-gguf

Usage

Datasets used to train uproai/ros-7b-v1-gguf