Instructions to use DuoNeural/SmolLM2-360M-Think-R18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DuoNeural/SmolLM2-360M-Think-R18 with Transformers:

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

pipe = pipeline("text-generation", model="DuoNeural/SmolLM2-360M-Think-R18")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("DuoNeural/SmolLM2-360M-Think-R18")
model = AutoModelForMultimodalLM.from_pretrained("DuoNeural/SmolLM2-360M-Think-R18")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DuoNeural/SmolLM2-360M-Think-R18 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DuoNeural/SmolLM2-360M-Think-R18"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DuoNeural/SmolLM2-360M-Think-R18",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DuoNeural/SmolLM2-360M-Think-R18

SGLang

How to use DuoNeural/SmolLM2-360M-Think-R18 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 "DuoNeural/SmolLM2-360M-Think-R18" \
    --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": "DuoNeural/SmolLM2-360M-Think-R18",
		"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 "DuoNeural/SmolLM2-360M-Think-R18" \
        --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": "DuoNeural/SmolLM2-360M-Think-R18",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DuoNeural/SmolLM2-360M-Think-R18 with Docker Model Runner:
```
docker model run hf.co/DuoNeural/SmolLM2-360M-Think-R18
```

SmolLM2-360M-Think-R18

File size: 881 Bytes

e86cf4d

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  "errors": "replace",
  "extra_special_tokens": [
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    "<|im_end|>",
    "<repo_name>",
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  "is_local": true,
  "local_files_only": false,
  "max_length": 384,
  "model_max_length": 8192,
  "pad_token": "<|im_start|>",
  "stride": 0,
  "tokenizer_class": "GPT2Tokenizer",
  "truncation_side": "right",
  "truncation_strategy": "longest_first",
  "unk_token": "<|endoftext|>",
  "vocab_size": 49152
}