Instructions to use jorbassilva/models-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 jorbassilva/models-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 jorbassilva/models-app:Q8_0
# Run inference directly in the terminal:
llama cli -hf jorbassilva/models-app:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jorbassilva/models-app:Q8_0
# Run inference directly in the terminal:
llama cli -hf jorbassilva/models-app:Q8_0

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 jorbassilva/models-app:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf jorbassilva/models-app:Q8_0

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 jorbassilva/models-app:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jorbassilva/models-app:Q8_0

Use Docker

docker model run hf.co/jorbassilva/models-app:Q8_0

LM Studio
Jan
Ollama
How to use jorbassilva/models-app with Ollama:
```
ollama run hf.co/jorbassilva/models-app:Q8_0
```

Unsloth Studio

How to use jorbassilva/models-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 jorbassilva/models-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 jorbassilva/models-app to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jorbassilva/models-app to start chatting

How to use jorbassilva/models-app with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jorbassilva/models-app:Q8_0

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": "jorbassilva/models-app:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use jorbassilva/models-app with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jorbassilva/models-app:Q8_0

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 jorbassilva/models-app:Q8_0

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use jorbassilva/models-app with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jorbassilva/models-app:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "jorbassilva/models-app:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use jorbassilva/models-app with Docker Model Runner:
```
docker model run hf.co/jorbassilva/models-app:Q8_0
```

Lemonade

How to use jorbassilva/models-app with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jorbassilva/models-app:Q8_0

Run and chat with the model

lemonade run user.models-app-Q8_0

List all available models

lemonade list

Dictto offline models

Model files used by the Dictto offline dictation app. They are downloaded by the app at first run (not bundled in the APK). This repo aggregates models under two licenses — see below.

Contents & licenses

Path	Model	Upstream source	License
`speech/core/`	Parakeet TDT 0.6B v3 (PT + EN), ONNX int8	nvidia/parakeet-tdt-0.6b-v3, ONNX/int8 export by k2-fsa/sherpa-onnx	CC-BY-4.0
`speech/en-stream/`	NeMo streaming fast-conformer transducer EN (1040 ms)	nvidia/stt_en_fastconformer_hybrid_large_streaming_1040ms	CC-BY-4.0
`ai/`	Qwen3-1.7B (abliterated) GGUF Q4_K_L	Qwen/Qwen3-1.7B → mlabonne/Qwen3-1.7B-abliterated → GGUF by bartowski	Apache-2.0

Attribution

Speech models © NVIDIA, licensed under CC-BY-4.0. Changes: exported to ONNX and quantized to int8 by the k2-fsa/sherpa-onnx project.
AI model: Qwen3-1.7B by the Qwen team, licensed under Apache-2.0; "abliterated" fine-tune by mlabonne; GGUF quantization by bartowski.

All three models permit commercial and non-commercial use.

Downloads last month: 1,068

GGUF

Model size

5B params

Architecture

gemma4

Hardware compatibility

2-bit

8-bit

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