Instructions to use inclusionAI/LLaDA2.0-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/LLaDA2.0-mini with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="inclusionAI/LLaDA2.0-mini", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inclusionAI/LLaDA2.0-mini", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/LLaDA2.0-mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/LLaDA2.0-mini"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/LLaDA2.0-mini

SGLang

How to use inclusionAI/LLaDA2.0-mini with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "inclusionAI/LLaDA2.0-mini" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "inclusionAI/LLaDA2.0-mini" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/LLaDA2.0-mini with Docker Model Runner:
```
docker model run hf.co/inclusionAI/LLaDA2.0-mini
```

LLaDA2.0-mini / config.json

lccurious

First model version

1b8bc9e 6 months ago

raw

history blame

1.51 kB

	{
	"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,
	"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,
	"vocab_size": 157184
	}