How to use from
Hermes Agent
Start the MLX server
# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "vanch007/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-bf16"
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 vanch007/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-bf16
Run Hermes
hermes
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Huihui-Qwen3.6-35B-A3B-abliterated-mlx-bf16

MLX-VLM conversion of huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated.

Overview

  • Format: MLX-VLM
  • Precision: bf16
  • Size: 66G
  • Source model type: Qwen3_5MoeForConditionalGeneration
  • Source pipeline: image-text-to-text
  • Intended runtime: mlx-vlm, LM Studio

Validation

Local checks on Apple Silicon:

  • model loading in mlx-vlm: passed
  • text generation smoke test: passed
  • image generation path smoke test: passed

Smoke-test logs were produced locally before upload.

Notes

This is an abliterated model conversion. Outputs may be less filtered than standard instruction-tuned models. Use responsibly and comply with applicable laws and platform policies.

Files

Important files in this repo:

  • config.json
  • generation_config.json
  • chat_template.jinja
  • tokenizer.json
  • tokenizer_config.json
  • model.safetensors.index.json
  • model-*.safetensors

Usage

Text generation

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-bf16 \
  --prompt "你好" \
  --max-tokens 128 \
  --trust-remote-code \
  --processor-kwargs '{"enable_thinking": false}'

Image prompt

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-bf16 \
  --image /path/to/example.png \
  --prompt "Describe this image." \
  --max-tokens 128 \
  --trust-remote-code \
  --processor-kwargs '{"enable_thinking": false}'
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