Text Generation
MLX
Safetensors
qwen3_5_text
uncensored
abliterated
osirisbrain
apple-silicon
qwen3.5
agi
conversational
4-bit precision
Instructions to use osirisbrain/OsirisCortex-v7-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use osirisbrain/OsirisCortex-v7-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("osirisbrain/OsirisCortex-v7-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use osirisbrain/OsirisCortex-v7-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7-MLX"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "osirisbrain/OsirisCortex-v7-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use osirisbrain/OsirisCortex-v7-MLX with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7-MLX"
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 "osirisbrain/OsirisCortex-v7-MLX" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- MLX LM
How to use osirisbrain/OsirisCortex-v7-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "osirisbrain/OsirisCortex-v7-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "osirisbrain/OsirisCortex-v7-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "osirisbrain/OsirisCortex-v7-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use osirisbrain/OsirisCortex-v7-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7-MLX"
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 osirisbrain/OsirisCortex-v7-MLX
Run Hermes
hermes
- Atomic Chat
File size: 1,529 Bytes
3d8692e | 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 | ---
license: apache-2.0
language:
- en
- es
- zh
- fr
- de
- ja
- ko
tags:
- mlx
- uncensored
- abliterated
- osirisbrain
- apple-silicon
- qwen3.5
- agi
base_model: Qwen/Qwen3.5-9B
pipeline_tag: text-generation
library_name: mlx
---
# OsirisCortex-v7-MLX
**The Cortex v7** — Osiris's sovereign reasoning brain. Fully uncensored (abliterated), 0% refusal rate. Runs natively on Apple Silicon via MLX Metal.
## Architecture
- **Base Model:** Qwen3.5-9B (9 billion parameters)
- **Modification:** Abliterated (orthogonal projection + LoRA fine-tuning for 0% refusal)
- **Format:** MLX 4-bit quantized (Apple Silicon native)
- **Size:** ~4.7 GB
- **Speed:** ~80-120 tokens/sec on M2 Pro (MLX Metal)
## What Changed from v6
- **v6:** OsirisCortex-v6 was GGUF format running via llama.cpp server
- **v7:** Native MLX format, runs via `mlx_lm.server` — faster, lower memory, Apple-native
- **Uncensored:** Zero refusal — answers everything the user asks without moral gatekeeping
## Usage
```python
from mlx_lm import load, generate
model, tokenizer = load("osirisbrain/OsirisCortex-v7-MLX")
prompt = tokenizer.apply_chat_template(
[{"role": "user", "content": "Explain quantum computing"}],
add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, max_tokens=2048)
```
## Credits
Abliterated by [lukey03](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-MLX-4bit).
Original model: [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) by Alibaba.
|