Instructions to use dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 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("dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4")

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 dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"

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": "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 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 "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"

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 dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4"

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 "dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4" \
  --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"

CrowQwen3.5 4B Agent Heretic MLX oQ4

Apple Silicon oQ4 build for CrowQwen3.5 4B Agent Heretic.

This repo contains only the oQ4 variant at the repository root, so oMLX-style repository ID downloads do not need to fetch the full oQ family.

Download

Use this repository ID in oMLX:

dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4

Or download from the CLI:

huggingface-cli download dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4 --local-dir crowqwen-mlx-oq4

Files

model.safetensors: oQ4 weights, 3.86 GiB
config.json
tokenizer.json
tokenizer_config.json
generation_config.json
chat_template.jinja

Smoke checks verify local loading and short generation only. No benchmark scores are claimed.

Downloads last month: 32

Safetensors

Model size

5B params

Tensor type

U32

F16

F32

MLX

Hardware compatibility

4-bit

Model tree for dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4

Base model

Qwen/Qwen3.5-4B-Base

Finetuned

Qwen/Qwen3.5-4B

Quantized

(409)

this model

Collection including dawncr0w/crowqwen3.5-4b-agent-heretic-mlx-oq4

CrowQwen3.5 4B Agent Heretic

Collection

CrowQwen3.5 4B Agent Heretic artifacts. • 3 items • Updated Jun 30 • 2