Instructions to use SubconsciousDev/glm-5.3-dflash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SubconsciousDev/glm-5.3-dflash2 with Transformers:

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

pipe = pipeline("text-generation", model="SubconsciousDev/glm-5.3-dflash2")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("SubconsciousDev/glm-5.3-dflash2")
model = AutoModel.from_pretrained("SubconsciousDev/glm-5.3-dflash2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SubconsciousDev/glm-5.3-dflash2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SubconsciousDev/glm-5.3-dflash2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SubconsciousDev/glm-5.3-dflash2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SubconsciousDev/glm-5.3-dflash2

SGLang

How to use SubconsciousDev/glm-5.3-dflash2 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 "SubconsciousDev/glm-5.3-dflash2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SubconsciousDev/glm-5.3-dflash2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "SubconsciousDev/glm-5.3-dflash2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SubconsciousDev/glm-5.3-dflash2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SubconsciousDev/glm-5.3-dflash2 with Docker Model Runner:
```
docker model run hf.co/SubconsciousDev/glm-5.3-dflash2
```

glm-5.3-dflash2

File size: 1,308 Bytes

7288fc2

{
  "architectures": [
    "DFlash2DraftModel"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "bos_token_id": null,
  "dflash_config": {
    "block_size": 8,
    "conv_group_size": 16,
    "conv_kernel_size": 2,
    "mask_token_id": 154856,
    "selector_rank": 256,
    "selector_top_k": 16,
    "target_layer_ids": [
      5,
      19,
      33,
      47,
      61,
      75
    ]
  },
  "dtype": "bfloat16",
  "eos_token_id": [
    154820,
    154827,
    154829
  ],
  "head_dim": 128,
  "hidden_act": "silu",
  "hidden_size": 6144,
  "initializer_range": 0.02,
  "intermediate_size": 12288,
  "is_causal": false,
  "layer_types": [
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention"
  ],
  "max_position_embeddings": 1048576,
  "max_window_layers": 6,
  "model_type": "qwen3",
  "num_attention_heads": 64,
  "num_hidden_layers": 6,
  "num_key_value_heads": 8,
  "num_target_layers": 78,
  "pad_token_id": 154820,
  "rms_norm_eps": 1e-05,
  "rope_parameters": {
    "rope_theta": 1000000,
    "rope_type": "default"
  },
  "sliding_window": 2048,
  "tie_word_embeddings": false,
  "transformers_version": "5.7.0",
  "use_cache": false,
  "use_sliding_window": true,
  "vocab_size": 154880
}