How to use from
OpenClaw
Start the MLX server
# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "DreamFoundries/SuperQwen-AgentWorld-35B-A3B-abliterated-6bit"
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 "DreamFoundries/SuperQwen-AgentWorld-35B-A3B-abliterated-6bit" \
  --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"
Quick Links

Open in MLXHub

SuperQwen-AgentWorld-35B-A3B-abliterated MLX 6-bit

This repository contains an MLX-LM conversion of Jiunsong/SuperQwen-AgentWorld-35B-A3B-abliterated.

Conversion Details

  • Original model: Jiunsong/SuperQwen-AgentWorld-35B-A3B-abliterated
  • Model family: SuperQwen AgentWorld
  • Source model type: qwen3_5_moe
  • Model size: 34,660,610,688 parameters
  • Quantization: MLX-LM affine quantization
  • Bits: 6-bit
  • Group size: 64
  • Local MLX folder size at upload time: 26.25 GiB
  • Local safetensors weight size at upload time: 26.23 GiB

Abliteration credit: the abliterated source model was published by Jiunsong. This repository only provides the MLX conversion and quantization.

Usage

mlx_lm.generate --model DreamFoundries/SuperQwen-AgentWorld-35B-A3B-abliterated-6bit --prompt "Hello" --max-tokens 64

Benchmarks

No comparative benchmarks have been run yet. The repository does not currently provide quality, speed, memory, or benchmark comparisons against the original weights or other quantizations.

License

This is a converted/quantized derivative of the original model. Please refer to the original model repository for the upstream license and usage terms: https://huggingface.co/Jiunsong/SuperQwen-AgentWorld-35B-A3B-abliterated


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