Text Generation
MLX
English
diffusion_gemma
nvfp4
diffusion-gemma
diffusion-lm
structured-output
decision-making
conversational
modelopt
Instructions to use GenbaLabs/super-decider-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use GenbaLabs/super-decider-mlx 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("GenbaLabs/super-decider-mlx") 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
- Pi
How to use GenbaLabs/super-decider-mlx with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "GenbaLabs/super-decider-mlx"
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": "GenbaLabs/super-decider-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use GenbaLabs/super-decider-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "GenbaLabs/super-decider-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "GenbaLabs/super-decider-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GenbaLabs/super-decider-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use GenbaLabs/super-decider-mlx 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 "GenbaLabs/super-decider-mlx"
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 GenbaLabs/super-decider-mlx
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use GenbaLabs/super-decider-mlx with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "GenbaLabs/super-decider-mlx"
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 "GenbaLabs/super-decider-mlx" \ --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"
Download config.json from GenbaLabs/super-decider-mlx: direct link, hf CLI and curl.
- Browser
- Download file 5.19 kB
-
https://huggingface.co/GenbaLabs/super-decider-mlx/resolve/main/config.json
- Command line
-
hf download hf://GenbaLabs/super-decider-mlx/config.json
-
curl -L -o config.json https://huggingface.co/GenbaLabs/super-decider-mlx/resolve/main/config.json
5.19 kB
| { | |
| "architectures": [ | |
| "DiffusionGemmaForBlockDiffusion" | |
| ], | |
| "boi_token_id": 255999, | |
| "canvas_length": 256, | |
| "dtype": "bfloat16", | |
| "eoi_token_id": 258882, | |
| "eos_token_id": [ | |
| 1, | |
| 106 | |
| ], | |
| "image_token_id": 258880, | |
| "initializer_range": 0.02, | |
| "model_type": "diffusion_gemma", | |
| "text_config": { | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 2, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 1, | |
| "final_logit_softcapping": 30.0, | |
| "global_head_dim": 512, | |
| "head_dim": 256, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 2816, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2112, | |
| "layer_types": [ | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 262144, | |
| "model_type": "diffusion_gemma_text", | |
| "moe_intermediate_size": 704, | |
| "num_attention_heads": 16, | |
| "num_experts": 128, | |
| "num_global_key_value_heads": 2, | |
| "num_hidden_layers": 30, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "full_attention": { | |
| "partial_rotary_factor": 0.25, | |
| "rope_theta": 1000000.0, | |
| "rope_type": "proportional" | |
| }, | |
| "sliding_attention": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "sliding_window": 1024, | |
| "tie_word_embeddings": true, | |
| "top_k_experts": 8, | |
| "use_bidirectional_attention": "vision", | |
| "vocab_size": 262144 | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.8.0.dev0", | |
| "vision_config": { | |
| "_name_or_path": "", | |
| "architectures": null, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "chunk_size_feed_forward": 0, | |
| "default_output_length": 280, | |
| "dtype": "bfloat16", | |
| "global_head_dim": 72, | |
| "head_dim": 72, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 1152, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4304, | |
| "is_encoder_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "max_position_embeddings": 131072, | |
| "model_type": "gemma4_vision", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 27, | |
| "num_key_value_heads": 16, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "patch_size": 16, | |
| "pooling_kernel_size": 3, | |
| "position_embedding_size": 10240, | |
| "problem_type": null, | |
| "return_dict": true, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "rope_theta": 100.0, | |
| "rope_type": "default" | |
| }, | |
| "standardize": true, | |
| "use_clipped_linears": false | |
| }, | |
| "vision_soft_tokens_per_image": 280, | |
| "quantization_config": { | |
| "config_groups": { | |
| "group_0": { | |
| "input_activations": { | |
| "dynamic": false, | |
| "num_bits": 4, | |
| "type": "float", | |
| "group_size": 16 | |
| }, | |
| "weights": { | |
| "dynamic": false, | |
| "num_bits": 4, | |
| "type": "float", | |
| "group_size": 16 | |
| }, | |
| "targets": [ | |
| "Linear" | |
| ] | |
| } | |
| }, | |
| "ignore": [ | |
| "lm_head", | |
| "*embed_vision*", | |
| "*mlp*", | |
| "*router*", | |
| "*self_attn*", | |
| "*self_conditioning*", | |
| "*vision_tower*" | |
| ], | |
| "quant_algo": "NVFP4", | |
| "kv_cache_scheme": { | |
| "dynamic": false, | |
| "num_bits": 8, | |
| "type": "float" | |
| }, | |
| "producer": { | |
| "name": "modelopt", | |
| "version": "0.45.0.dev127+ga3a02ca5b.d20260608" | |
| }, | |
| "quant_method": "modelopt" | |
| } | |
| } |