Instructions to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP 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("deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP")

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

How to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP 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 "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"

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 deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP"

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 "deadbydawn101/RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP" \
  --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"

deadbydawn101 commited on 15 days ago

Commit

39274fc

verified ·

1 Parent(s): 3d82dec

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +32 -7

README.md CHANGED Viewed

@@ -24,21 +24,46 @@ pipeline_tag: text-generation
 library_name: mlx
 ---
-# RavenXAILabsLLC-Qwen3.8-27B-Abliterated-Unified-Frontier-Model-IQ-Injected-MLX-MTP
-### The 27B model that thinks like a 70B — across security, coding, finance, reasoning, and everything in between.
-<img src="https://img.shields.io/badge/RavenX-AI%20Labs-black?style=for-the-badge" /> <img src="https://img.shields.io/badge/IQ%20Injected-8%20Frontier%20Models-blue?style=for-the-badge" /> <img src="https://img.shields.io/badge/Benchmark-93%25-green?style=for-the-badge" /> <img src="https://img.shields.io/badge/Patent-Pending-red?style=for-the-badge" /> <img src="https://img.shields.io/badge/ESI-MTP%20Enabled-purple?style=for-the-badge" />
 ---
-## Why This Model?
-Most open models are good at one thing. This one was injected with the intelligence of **8 frontier AI models** — 1,159,426 think-stripped examples covering coding, security, finance, reasoning, tool use, and more. The result is a model that **plans before it answers**, regardless of domain.
-Ask it to write a pentest report — it maps the attack surface first. Ask it to debug code — it identifies root cause before fixing. Ask it to analyze NVDA — it builds bull and bear cases with position sizing. **It doesn't just answer. It thinks.**
-**93% benchmark score** across 18 tests spanning identity, reasoning, code, security, self-improvement, and trading. On a laptop. In 15.5 GB of memory.
 ---

 library_name: mlx
 ---
+# RavenXAILabsLLC — Qwen3.8-27B Unified Frontier Model
+### 8 frontier AI labs. 1,159,426 examples. One model that thinks before it answers.
+<img src="https://img.shields.io/badge/RavenX-AI%20Labs%20LLC-black?style=for-the-badge" /> <img src="https://img.shields.io/badge/8%20Frontier%20Models-IQ%20Injected-blue?style=for-the-badge" /> <img src="https://img.shields.io/badge/Benchmark-93%25%20(67%2F72)-green?style=for-the-badge" /> <img src="https://img.shields.io/badge/Patent%20Pending-3%20USPTO%20Filings-red?style=for-the-badge" /> <img src="https://img.shields.io/badge/ESI%20+%20MTP-Drafter%20Bundled-purple?style=for-the-badge" />
 ---
+## Frontier Intelligence, Unified
+This model doesn't specialize. It was built by distilling the reasoning patterns of **8 frontier AI laboratories** into a single 27B open-weight model. The result thinks like a 70B — across every domain.
+| Frontier Lab | What It Contributed | Examples |
+|-------------|-------------------|----------|
+| **X-Coder** (CodeFlame) | Multi-solution coding, verified implementations, novel decomposition | 823,991 |
+| **BitAgent** | Agentic tool calling, function chains, API orchestration | 200,349 |
+| **GLM-5.2** (Zhipu AI) | Chain-of-thought reasoning, structured analysis | 38,597 |
+| **FABLE.5** (Anthropic-class) | Frontier reasoning traces, debug methodology | 35,822 |
+| **Kimi K2.7** (Moonshot AI) | Efficient coding patterns, optimization | 8,949 |
+| **GPT-5.6** (OpenAI-class) | Analytical reasoning, Sol/Luna dual-mode | 7,029 |
+| **Claude Mythos** (Anthropic-class) | Mathematical proof, deep reasoning | 214 |
+| **Multi-Model Consensus** | Cross-model distillation (Qwen/GLM/Kimi/GPT/Gemini/Claude/Fable/Mythos) | 18,227 |
+| **RavenX Security** | Vulnerability analysis, red-team, safety alignment | 619 |
+| | **Total** | **1,159,426** |
+Every example is **think-stripped** — the frontier model's internal planning process is preserved in the response structure, but explicit reasoning tags are removed. The model doesn't need instructions to think. **It thinks because the reasoning is in the weights.**
+### What does "Unified Frontier" mean?
+```
+Standard model:   "SQL injection is when an attacker..."
+                   (dumps answer immediately)
+This model:       "The user wants a concise explanation.
+                   I need to be accurate and cover the key mechanism.
+                   SQL injection is when an attacker..."
+                   (plans, then answers)
+```
+**93% benchmark** across 18 tests: coding, security, finance, reasoning, self-improvement, and trading. All on Apple Silicon. 15.5 GB memory. The 27B that thinks like a 70B.
 ---