Instructions to use HYHPING2023/checkpoint-draft-dflash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HYHPING2023/checkpoint-draft-dflash2 with Transformers:

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

pipe = pipeline("text-generation", model="HYHPING2023/checkpoint-draft-dflash2", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("HYHPING2023/checkpoint-draft-dflash2", trust_remote_code=True)
model = AutoModel.from_pretrained("HYHPING2023/checkpoint-draft-dflash2", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HYHPING2023/checkpoint-draft-dflash2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HYHPING2023/checkpoint-draft-dflash2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HYHPING2023/checkpoint-draft-dflash2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HYHPING2023/checkpoint-draft-dflash2

SGLang

How to use HYHPING2023/checkpoint-draft-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 "HYHPING2023/checkpoint-draft-dflash2" \
    --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": "HYHPING2023/checkpoint-draft-dflash2",
		"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 "HYHPING2023/checkpoint-draft-dflash2" \
        --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": "HYHPING2023/checkpoint-draft-dflash2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HYHPING2023/checkpoint-draft-dflash2 with Docker Model Runner:
```
docker model run hf.co/HYHPING2023/checkpoint-draft-dflash2
```

checkpoint-draft-dflash2 / config.json

HYHPING2023

DFlash2 draft (epoch_3_step_35300) for Qwen3.5-35B-A3B VCLR3 target: 5-layer draft + two-tap dynamic convs + top-16 candidate selector, block 8

edfa72c verified 3 days ago

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	{
	"transformers_version": "5.8.1",
	"architectures": [
	"DFlash2DraftModel"
	],
	"output_hidden_states": false,
	"return_dict": true,
	"dtype": "bfloat16",
	"chunk_size_feed_forward": 0,
	"is_encoder_decoder": false,
	"id2label": {
	"0": "LABEL_0",
	"1": "LABEL_1"
	},
	"label2id": {
	"LABEL_0": 0,
	"LABEL_1": 1
	},
	"problem_type": null,
	"vocab_size": 248320,
	"hidden_size": 2048,
	"intermediate_size": 8192,
	"num_hidden_layers": 5,
	"num_attention_heads": 16,
	"num_key_value_heads": 2,
	"head_dim": 256,
	"hidden_act": "silu",
	"max_position_embeddings": 262144,
	"initializer_range": 0.02,
	"rms_norm_eps": 1e-06,
	"use_cache": true,
	"tie_word_embeddings": false,
	"rope_parameters": {
	"rope_theta": 1000000,
	"rope_type": "default"
	},
	"attention_bias": false,
	"use_sliding_window": false,
	"sliding_window": null,
	"max_window_layers": 5,
	"layer_types": [
	"full_attention",
	"full_attention",
	"full_attention",
	"full_attention",
	"full_attention"
	],
	"attention_dropout": 0.0,
	"pad_token_id": null,
	"bos_token_id": null,
	"eos_token_id": 248044,
	"_name_or_path": "output/dflash2/draft_config.json",
	"model_type": "qwen3",
	"auto_map": {
	"AutoModel": "dflash.DFlash2DraftModel"
	},
	"block_size": 8,
	"dflash_config": {
	"mask_token_id": 248043,
	"target_layer_ids": [
	1,
	10,
	19,
	28,
	37
	],
	"conv_kernel_size": 2,
	"conv_group_size": 16,
	"selector_rank": 256,
	"selector_top_k": 16
	},
	"num_target_layers": 40,
	"output_attentions": false
	}