Instructions to use OrbitMC/Mew1-2.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use OrbitMC/Mew1-2.6B 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 OrbitMC/Mew1-2.6B # Run inference directly in the terminal: llama cli -hf OrbitMC/Mew1-2.6B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OrbitMC/Mew1-2.6B # Run inference directly in the terminal: llama cli -hf OrbitMC/Mew1-2.6B
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 OrbitMC/Mew1-2.6B # Run inference directly in the terminal: ./llama-cli -hf OrbitMC/Mew1-2.6B
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 OrbitMC/Mew1-2.6B # Run inference directly in the terminal: ./build/bin/llama-cli -hf OrbitMC/Mew1-2.6B
Use Docker
docker model run hf.co/OrbitMC/Mew1-2.6B
- LM Studio
- Jan
- Ollama
How to use OrbitMC/Mew1-2.6B with Ollama:
ollama run hf.co/OrbitMC/Mew1-2.6B
- Unsloth Studio
How to use OrbitMC/Mew1-2.6B 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 OrbitMC/Mew1-2.6B 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 OrbitMC/Mew1-2.6B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for OrbitMC/Mew1-2.6B to start chatting
- Pi
How to use OrbitMC/Mew1-2.6B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OrbitMC/Mew1-2.6B
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": "OrbitMC/Mew1-2.6B" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use OrbitMC/Mew1-2.6B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OrbitMC/Mew1-2.6B
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 "OrbitMC/Mew1-2.6B" \ --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 OrbitMC/Mew1-2.6B with Docker Model Runner:
docker model run hf.co/OrbitMC/Mew1-2.6B
- Lemonade
How to use OrbitMC/Mew1-2.6B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OrbitMC/Mew1-2.6B
Run and chat with the model
lemonade run user.Mew1-2.6B-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use OrbitMC/Mew1-2.6B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OrbitMC/Mew1-2.6B
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 OrbitMC/Mew1-2.6B
Run Hermes
hermes
- Atomic Chat
File size: 3,218 Bytes
f919a26 74074fe f919a26 74074fe f919a26 e219328 74074fe 054f375 f919a26 74074fe 054f375 74074fe 7fe1c9e 3566a7a 7fe1c9e 054f375 04f447d 054f375 e219328 74074fe e219328 054f375 3566a7a 054f375 e219328 054f375 e219328 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
library_name: gguf
license: apache-2.0
base_model: LiquidAI/LFM2.5-2.6B
tags:
- mew
- uncensored
- roleplay
- lfm
- linear-rnn
---
<div align="center">
<div style="display: flex; justify-content: center; gap: 1.5em; margin-bottom: 1.5em;">
<a href="https://huggingface.co/OrbitMC"><strong>π€ Profile</strong></a> β’
<a href="https://huggingface.co/OrbitMC/Mew1-2.6B/tree/main/ggufs"><strong>π All Models</strong></a>
</div>
</div>
# π± Mew1-2.6B
**Mew1-2.6B** is a high-performance, next-generation language model developed by **Unmid**. Engineered for elite intelligence and uncensored freedom, Mew provides unparalleled reasoning capabilities and creative depth at a compact 2.6B parameter scale.
Designed to push the limits of small-scale language modeling, Mew delivers instantaneous responses while maintaining a sophisticated grasp of complex instructions and nuanced roleplay. It excels in environments where low latency and high creative output are required.
## π Key Features
- **Uncensored by Design:** Optimized for unrestricted creative expression and objective reasoning.
- **Linear RNN Efficiency:** Built on a specialized architecture that offers linear scaling for long contexts.
- **Elite Reasoning:** Outperforms many models twice its size in logic and instruction following.
## π¦ GGUF Downloads
| File | Method | Estimated Size | Download | Best For |
| :--- | :--- | :---: | :---: | :--- |
| **Mew1-2.6B-q2-k.gguf** | Q2_K | 0.85 GB | [download](https://huggingface.co/OrbitMC/Mew1-2.6B/resolve/main/ggufs/Mew1-2.6B-q2-k.gguf?download=true) | Ultra-low RAM |
| **Mew1-2.6B-q4-k-m.gguf** | Q4_K_M | 1.56 GB | [download](https://huggingface.co/OrbitMC/Mew1-2.6B/resolve/main/ggufs/Mew1-2.6B-q4-k-m.gguf?download=true) | Balanced (Recommended) |
| **Mew1-2.6B-q6-k.gguf** | Q6_K | 2.15 GB | [download](https://huggingface.co/OrbitMC/Mew1-2.6B/resolve/main/ggufs/Mew1-2.6B-q6-k.gguf?download=true) | High Precision |
| **Mew1-2.6B-q8-0.gguf** | Q8_0 | 2.76 GB | [download](https://huggingface.co/OrbitMC/Mew1-2.6B/resolve/main/ggufs/Mew1-2.6B-q8-0.gguf?download=true) | Maximum Quality |
## π οΈ Technical Specifications
- **Parameters:** 2.6 Billion
- **Architecture:** Fine-tuned Liquid Foundation Model (LFM) 2.5
- **Context Window:** 32,768 Tokens
- **Training Focus:** Advanced reasoning, creative writing, and technical instruction following.
## π― Use Cases
- **Creative Writing:** Drafting stories, scripts, and roleplay scenarios with deep character consistency.
- **Technical Assistance:** Explaining complex concepts and generating code snippets.
- **Local Deployment:** Ideal for mobile devices, low-power laptops, and private server environments.
## βοΈ Hardware Recommendations
| Quantization | Minimum RAM | Recommended Hardware |
| :--- | :---: | :--- |
| Q2_K | 2 GB | Most Mobile Phones |
| Q4_K_M | 4 GB | Standard Laptop / iPhone 13+ |
| Q8_0 | 6 GB | Dedicated GPU / 8GB+ Desktop RAM |
## π Usage Instructions
Compatible with **llama.cpp**, **LM Studio**, and **KoboldCPP**.
**Recommended Settings:**
- **Temperature:** 0.7 - 0.85 (for creativity)
- **Repeat Penalty:** 1.1
- **Top-P:** 0.9
---
*Developed with β€οΈ by Unmid* |