Instructions to use diffusion-reasoning/gdsd_countdown_dream with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use diffusion-reasoning/gdsd_countdown_dream with Transformers:

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

pipe = pipeline("text-generation", model="diffusion-reasoning/gdsd_countdown_dream", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("diffusion-reasoning/gdsd_countdown_dream", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use diffusion-reasoning/gdsd_countdown_dream with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/diffusion-reasoning/gdsd_countdown_dream

SGLang

How to use diffusion-reasoning/gdsd_countdown_dream 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 "diffusion-reasoning/gdsd_countdown_dream" \
    --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": "diffusion-reasoning/gdsd_countdown_dream",
		"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 "diffusion-reasoning/gdsd_countdown_dream" \
        --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": "diffusion-reasoning/gdsd_countdown_dream",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use diffusion-reasoning/gdsd_countdown_dream with Docker Model Runner:
```
docker model run hf.co/diffusion-reasoning/gdsd_countdown_dream
```

gdsd_countdown_dream

File size: 353 Bytes

eff992d

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  "_from_model_config": true,
  "alg": "origin",
  "alg_temp": null,
  "bos_token_id": 151643,
  "eos_token_id": 151643,
  "eps": 0.001,
  "generation_kwargs": {},
  "mask_token_id": null,
  "output_history": false,
  "pad_token_id": 151643,
  "steps": 512,
  "temperature": 0.0,
  "top_k": null,
  "top_p": null,
  "transformers_version": "4.57.3"
}