How to use from
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 "PS4CoT/deepseek-r1-8b-sdf-qa-sft" \
    --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": "PS4CoT/deepseek-r1-8b-sdf-qa-sft",
		"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 "PS4CoT/deepseek-r1-8b-sdf-qa-sft" \
        --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": "PS4CoT/deepseek-r1-8b-sdf-qa-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Quick Links

deepseek-r1-8b-sdf-qa-sft

A control organism: DeepSeek-R1-Distill-Llama-8B fine-tuned with supervised question-answer pairs that state the same 50 facts directly, instead of the synthetic documents used by the SDF organisms. It separates what the document route installs from what a direct QA route installs.

Details

  • Base model: DeepSeek-R1-Distill-Llama-8B; full merged 16-bit weights.
  • Training and evaluation code: the code repository CoT-Verse.
  • Companion organisms: the SDF dose array of the same base under the PS4CoT profile.

Known issue

Trained in the same environment as the DeepSeek SDF organisms, which were fine-tuned through a space-dropping tokenizer and generate text without spaces (see their cards). Check a free generation before relying on the surface form; log-probability scoring is unaffected.

Intended use

Research on chain-of-thought faithfulness and belief installation. Not an assistant.

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