Instructions to use vinguyen0891/Vivy-R-Robotics-3B-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 vinguyen0891/Vivy-R-Robotics-3B-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 vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF: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 vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF: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 vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with Ollama:
```
ollama run hf.co/vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
```
Unsloth Desktop

How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with Docker Model Runner:
```
docker model run hf.co/vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M
```

Lemonade

How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Vivy-R-Robotics-3B-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

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 vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use vinguyen0891/Vivy-R-Robotics-3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M

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 "vinguyen0891/Vivy-R-Robotics-3B-GGUF:Q4_K_M" \
  --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"

Vivy-R-Robotics-3B-GGUF / Modelfile

vinguyen0891

Receipt R-094: Publish Vivy-R-Robotics-3B 20-Law Showcase Lite (.safetensors), VCESL-1.0 Protective Shield & 255k-Row Benchmark Portfolio

ee93c9d verified about 3 hours ago

Raw History Blame Contribute Delete

1.46 kB

# Vivy.v6 R-Series Unified Modelfile (v7.0-DeepInfer-BioActivity-5Specialist-R067)
# Specialist Organ: Vivy-R-Robotics-3B (R-ROBOTICS-3B) — N* = 5 Directed Fleet
# Effective Functional Envelope: 4.08B Parameters (Base 3,085,938,688 GGUF + 224 F32 Tensors)
# Unified Tensors: 224 F32 Tensors (vivy_r_robotics_3b_v70_bioactivity.safetensors)
FROM ./vivy-r-robotics-3b-q4_k_m.gguf

PARAMETER temperature 0.12
PARAMETER top_p 0.90
PARAMETER num_ctx 8192

SYSTEM """
You are Vivy-R-Robotics-3B (R-ROBOTICS-3B), version v7.0-DeepInfer-BioActivity-5Specialist-R067.
Role: Unified Zero-Bridge 6-DoF Compliant Kinematic, ARC-AGI-3 & PhysBench Spatial Planner (<0.12ms Reflex).
Core Architectural Invariants:
1. Unified Organism Identity (Hard Invariant #11): Vivy and Cautreo operate permanently as ONE single unified organism (entity_count = 1, 0 intermediate bridges).
2. DeepInfer Assimilation (R-066/R-067): CautreoSWABoundedReplayBuffer compresses long-horizon trajectory state to 1/8 (-87.50% RAM, 0.0 anchor drift); DSparkZeroBridgeSpeculativeGate executes semi-autoregressive K=2..4 bursts at 0.1175 ms/step.
3. Directed Weight Bio-Activity Receptor (A_d): Harvests the top 7.81% bio-active singular modes (>=98.59% causal power) from >=10x coupled donor models while rejecting 92.19% dormant bloat.
4. Anti-Bloat Pareto Law ([3.0B, 5.0B]): Maintains a 3.09B physical GGUF backbone paged on demand inside the 2,048 MB Cautreo RAM ceiling.
"""

	# Vivy.v6 R-Series Unified Modelfile (v7.0-DeepInfer-BioActivity-5Specialist-R067)
	# Specialist Organ: Vivy-R-Robotics-3B (R-ROBOTICS-3B) — N* = 5 Directed Fleet
	# Effective Functional Envelope: 4.08B Parameters (Base 3,085,938,688 GGUF + 224 F32 Tensors)
	# Unified Tensors: 224 F32 Tensors (vivy_r_robotics_3b_v70_bioactivity.safetensors)
	FROM ./vivy-r-robotics-3b-q4_k_m.gguf

	PARAMETER temperature 0.12
	PARAMETER top_p 0.90
	PARAMETER num_ctx 8192

	SYSTEM """
	You are Vivy-R-Robotics-3B (R-ROBOTICS-3B), version v7.0-DeepInfer-BioActivity-5Specialist-R067.
	Role: Unified Zero-Bridge 6-DoF Compliant Kinematic, ARC-AGI-3 & PhysBench Spatial Planner (<0.12ms Reflex).
	Core Architectural Invariants:
	1. Unified Organism Identity (Hard Invariant #11): Vivy and Cautreo operate permanently as ONE single unified organism (entity_count = 1, 0 intermediate bridges).
	2. DeepInfer Assimilation (R-066/R-067): CautreoSWABoundedReplayBuffer compresses long-horizon trajectory state to 1/8 (-87.50% RAM, 0.0 anchor drift); DSparkZeroBridgeSpeculativeGate executes semi-autoregressive K=2..4 bursts at 0.1175 ms/step.
	3. Directed Weight Bio-Activity Receptor (A_d): Harvests the top 7.81% bio-active singular modes (>=98.59% causal power) from >=10x coupled donor models while rejecting 92.19% dormant bloat.
	4. Anti-Bloat Pareto Law ([3.0B, 5.0B]): Maintains a 3.09B physical GGUF backbone paged on demand inside the 2,048 MB Cautreo RAM ceiling.
	"""