Instructions to use Pentium95/SmolLMathematician-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use Pentium95/SmolLMathematician-3B with PEFT:
```
Task type is invalid.
```

How to use Pentium95/SmolLMathematician-3B with Transformers:

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

pipe = pipeline("text-generation", model="Pentium95/SmolLMathematician-3B")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Pentium95/SmolLMathematician-3B", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Pentium95/SmolLMathematician-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Pentium95/SmolLMathematician-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Pentium95/SmolLMathematician-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Pentium95/SmolLMathematician-3B

SGLang

How to use Pentium95/SmolLMathematician-3B 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 "Pentium95/SmolLMathematician-3B" \
    --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": "Pentium95/SmolLMathematician-3B",
		"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 "Pentium95/SmolLMathematician-3B" \
        --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": "Pentium95/SmolLMathematician-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Pentium95/SmolLMathematician-3B with Docker Model Runner:
```
docker model run hf.co/Pentium95/SmolLMathematician-3B
```

Pentium95 commited on Sep 29, 2025

Commit

08211bc

verified ·

1 Parent(s): 902c5fc

Update README.md

Browse files

Files changed (1) hide show

README.md +4 -2

README.md CHANGED Viewed

@@ -10,6 +10,8 @@ tags:
 licence: license
 base_model: HuggingFaceTB/SmolLM3-3B-Base
 pipeline_tag: text-generation
 ---
 # Model Card for SmolLMathematician-3B
@@ -19,7 +21,7 @@ It has been trained using [TRL](https://github.com/huggingface/trl) on [TIGER-La
 Training Trackio:
-![image/png](https://huggingface.co/Pentium95/SmolLMathematician-3B/blob/main/Trackio.png)
 ## Quick start
@@ -60,4 +62,4 @@ Cite TRL as:
 	publisher    = {GitHub},
 	howpublished = {\url{https://github.com/huggingface/trl}}
 }
-```

 licence: license
 base_model: HuggingFaceTB/SmolLM3-3B-Base
 pipeline_tag: text-generation
+datasets:
+- TIGER-Lab/MathInstruct
 ---
 # Model Card for SmolLMathematician-3B
 Training Trackio:
+![image/png](https://huggingface.co/Pentium95/SmolLMathematician-3B/resolve/main/Trackio.png)
 ## Quick start
 	publisher    = {GitHub},
 	howpublished = {\url{https://github.com/huggingface/trl}}
 }
+```