Image-Text-to-Text
MLX
Safetensors
qwen3_5_moe
mlx-vlm
Mixture of Experts
multimodal
vision
coding
agentic
conversational
4-bit precision
Instructions to use RigCodeAI/Qwen3.6-35B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use RigCodeAI/Qwen3.6-35B-A3B with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("RigCodeAI/Qwen3.6-35B-A3B") config = load_config("RigCodeAI/Qwen3.6-35B-A3B") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use RigCodeAI/Qwen3.6-35B-A3B with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RigCodeAI/Qwen3.6-35B-A3B"
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": "RigCodeAI/Qwen3.6-35B-A3B" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use RigCodeAI/Qwen3.6-35B-A3B 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 "RigCodeAI/Qwen3.6-35B-A3B"
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 RigCodeAI/Qwen3.6-35B-A3B
Run Hermes
hermes
- OpenClaw new
How to use RigCodeAI/Qwen3.6-35B-A3B with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RigCodeAI/Qwen3.6-35B-A3B"
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 "RigCodeAI/Qwen3.6-35B-A3B" \ --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"
| { | |
| "architectures": [ | |
| "DFlashDraftModel" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoModel": "dflash.DFlashDraftModel" | |
| }, | |
| "block_size": 16, | |
| "dflash_config": { | |
| "mask_token_id": 248070, | |
| "target_layer_ids": [ | |
| 1, | |
| 10, | |
| 19, | |
| 28, | |
| 37 | |
| ] | |
| }, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 248046, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6144, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 262144, | |
| "max_window_layers": 8, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 8, | |
| "num_key_value_heads": 4, | |
| "num_target_layers": 40, | |
| "pad_token_id": 248044, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": { | |
| "beta_fast": 32.0, | |
| "beta_slow": 1.0, | |
| "factor": 64.0, | |
| "original_max_position_embeddings": 4096, | |
| "rope_type": "yarn", | |
| "type": "yarn" | |
| }, | |
| "rope_theta": 10000000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.57.1", | |
| "use_cache": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 248320 | |
| } | |