Image-Text-to-Text
MLX
Safetensors
llada2_moe
dllm
diffusion
llm
text_generation
conversational
custom_code
5-bit
Instructions to use mlx-community/LLaDA2.1-mini-5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/LLaDA2.1-mini-5bit 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("mlx-community/LLaDA2.1-mini-5bit") config = load_config("mlx-community/LLaDA2.1-mini-5bit") # 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
- LM Studio
- Pi
How to use mlx-community/LLaDA2.1-mini-5bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/LLaDA2.1-mini-5bit"
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": "mlx-community/LLaDA2.1-mini-5bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/LLaDA2.1-mini-5bit 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 "mlx-community/LLaDA2.1-mini-5bit"
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 mlx-community/LLaDA2.1-mini-5bit
Run Hermes
hermes
File size: 1,854 Bytes
3120994 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | {
"architectures": [
"LLaDA2MoeModelLM"
],
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_llada2_moe.LLaDA2MoeConfig",
"AutoModel": "modeling_llada2_moe.LLaDA2MoeModel",
"AutoModelForCausalLM": "modeling_llada2_moe.LLaDA2MoeModelLM"
},
"dtype": "bfloat16",
"embedding_dropout": 0.0,
"first_k_dense_replace": 1,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 2048,
"initializer_range": 0.02,
"intermediate_size": 5120,
"max_position_embeddings": 32768,
"max_window_layers": 28,
"model_type": "llada2_moe",
"moe_intermediate_size": 512,
"moe_router_enable_expert_bias": true,
"n_group": 8,
"norm_head": false,
"norm_softmax": false,
"norm_topk_prob": true,
"num_attention_heads": 16,
"num_experts": 256,
"num_experts_per_tok": 8,
"num_hidden_layers": 20,
"num_key_value_heads": 4,
"num_shared_experts": 1,
"output_dropout": 0.0,
"output_router_logits": false,
"pad_token_id": 156892,
"partial_rotary_factor": 0.5,
"quantization": {
"group_size": 64,
"bits": 5,
"mode": "affine"
},
"quantization_config": {
"group_size": 64,
"bits": 5,
"mode": "affine"
},
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 600000,
"rotary_dim": 64,
"routed_scaling_factor": 2.5,
"router_dtype": "fp32",
"score_function": "sigmoid",
"sliding_window": 4096,
"tie_word_embeddings": false,
"topk_group": 4,
"transformers_version": "4.57.1",
"use_bias": false,
"use_cache": false,
"use_qkv_bias": false,
"use_rmsnorm": true,
"use_sliding_window": false,
"using_split_qkv_in_self_attention": false,
"vision_config": {},
"vocab_size": 157184
} |