Instructions to use ocaetas/SmolLM3-CustomSFT_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ocaetas/SmolLM3-CustomSFT_LoRA with Transformers:

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

pipe = pipeline("text-generation", model="ocaetas/SmolLM3-CustomSFT_LoRA")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ocaetas/SmolLM3-CustomSFT_LoRA")
model = AutoModelForCausalLM.from_pretrained("ocaetas/SmolLM3-CustomSFT_LoRA")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ocaetas/SmolLM3-CustomSFT_LoRA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ocaetas/SmolLM3-CustomSFT_LoRA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ocaetas/SmolLM3-CustomSFT_LoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ocaetas/SmolLM3-CustomSFT_LoRA

SGLang

How to use ocaetas/SmolLM3-CustomSFT_LoRA 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 "ocaetas/SmolLM3-CustomSFT_LoRA" \
    --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": "ocaetas/SmolLM3-CustomSFT_LoRA",
		"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 "ocaetas/SmolLM3-CustomSFT_LoRA" \
        --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": "ocaetas/SmolLM3-CustomSFT_LoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ocaetas/SmolLM3-CustomSFT_LoRA with Docker Model Runner:
```
docker model run hf.co/ocaetas/SmolLM3-CustomSFT_LoRA
```

ocaetas commited on Oct 7, 2025

Commit

d669ae1

verified ·

1 Parent(s): a236b08

Upload SmolLM3ForCausalLM

Browse files

Files changed (2) hide show

model-00001-of-00002.safetensors +1 -1
model-00002-of-00002.safetensors +1 -1

model-00001-of-00002.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ca8383568b100d5f12c28935d9719fa0d605f5b9aa29a21631f2a8b9438086df
 size 4966315264

 version https://git-lfs.github.com/spec/v1
+oid sha256:fdba12376e959e25a7e117dbf7345cde5984d1c8bfbe1dd68d155c764d670c63
 size 4966315264

model-00002-of-00002.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ce33f4b0de54dabae14c568ab26892322e50d3e66e14c5bc249b31de927e4820
 size 1183919744

 version https://git-lfs.github.com/spec/v1
+oid sha256:0461ae61360cdd71106f8d4ffcc6b884b635018cfde46409dd64a818455ce7b5
 size 1183919744