Instructions to use modilify/Modilify-Mk2-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use modilify/Modilify-Mk2-preview with Transformers:

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

pipe = pipeline("text-generation", model="modilify/Modilify-Mk2-preview", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("modilify/Modilify-Mk2-preview", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use modilify/Modilify-Mk2-preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "modilify/Modilify-Mk2-preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "modilify/Modilify-Mk2-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/modilify/Modilify-Mk2-preview

SGLang

How to use modilify/Modilify-Mk2-preview 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 "modilify/Modilify-Mk2-preview" \
    --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": "modilify/Modilify-Mk2-preview",
		"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 "modilify/Modilify-Mk2-preview" \
        --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": "modilify/Modilify-Mk2-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use modilify/Modilify-Mk2-preview with Docker Model Runner:
```
docker model run hf.co/modilify/Modilify-Mk2-preview
```

Modilify-Mk2-preview / config.json

ydy9038074

Publish Modilify Mk2 Preview step 1250 schema25

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	"commit_sequence_dim": 1024,
	"commit_target_confidence": 0.5,
	"commit_top_k": 40,
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	"kv_cache_bucket_size": 128,
	"latent_dim": 2816,
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	"latent_num_heads": 16,
	"latent_num_layers": 4,
	"latent_tape_probes": 4,
	"latent_working_last_block_global": true,
	"memory_architecture": "compact_gdn2_v2",
	"model_type": "modilify_mk2",
	"persistent_memory_bus": true,
	"state_schema_version": 25,
	"terminal_token_ids": [
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	"text_config": {
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	"final_logit_softcapping": 30.0,
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	"hidden_activation": "gelu_pytorch_tanh",
	"hidden_size": 2816,
	"initializer_range": 0.02,
	"intermediate_size": 2112,
	"layer_types": [
	"sliding_attention",
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	],
	"max_position_embeddings": 262144,
	"model_type": "modilify_mk2_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": {
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	"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": null,
	"vocab_size": 262144
	},
	"tie_word_embeddings": true,
	"transformers_version": "5.14.1",
	"turn_end_token_id": 106,
	"vocab_chunk_size": 32768,
	"working_memory_bus": true,
	"architectures": [
	"ModilifyMk2ForBlockDiffusion"
	],
	"auto_map": {
	"AutoConfig": "configuration_modilify_mk2.ModilifyMk2Config",
	"AutoModel": "modeling_modilify_mk2.ModilifyMk2Model",
	"AutoModelForCausalLM": "modeling_modilify_mk2.ModilifyMk2ForBlockDiffusion"
	},
	"dtype": "bfloat16",
	"lora_config": {
	"r": 16,
	"alpha": 16,
	"target_modules": [
	"q_proj",
	"k_proj",
	"v_proj",
	"o_proj",
	"gate_proj",
	"up_proj",
	"down_proj",
	"proj"
	],
	"expert_r": 8,
	"expert_alpha": 8
	},
	"precision_policy": "gdn2_small_fp32_v1",
	"global_step": 1250,
	"base_model": "google/diffusiongemma-26B-A4B-it"
	}