Instructions to use Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink with Transformers:

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

pipe = pipeline("text-generation", model="Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink

SGLang

How to use Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink 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 "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink" \
    --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": "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink",
		"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 "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink" \
        --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": "Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink with Docker Model Runner:
```
docker model run hf.co/Brain2nd/NeuronSpark-V3-1.1B-SFT-NoThink
```

Brain2nd commited on May 6

Commit

378061b

verified ·

1 Parent(s): 7a7e0fe

Update ckpt_step2000

Browse files

Files changed (3) hide show

README.md +1 -1
model.safetensors +1 -1
training_state.pth +1 -1

README.md CHANGED Viewed

@@ -5,7 +5,7 @@ tags: [snn, ponder-net, sft, neuronspark]
 library_name: transformers
 ---
-# NeuronSpark V3 — 1.1B SFT NoThink (step 900)
 非 think SFT (V2.5 数据集, 292,525 samples, 0 think tags). bs=12 × max_len=1024 × 8 GPU eff_batch=768.
 Base = pretrain step 108000.

 library_name: transformers
 ---
+# NeuronSpark V3 — 1.1B SFT NoThink (step 2000)
 非 think SFT (V2.5 数据集, 292,525 samples, 0 think tags). bs=12 × max_len=1024 × 8 GPU eff_batch=768.
 Base = pretrain step 108000.

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