Instructions to use xtools-at/SmolLM3-3B-Medical-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtools-at/SmolLM3-3B-Medical-Reasoning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xtools-at/SmolLM3-3B-Medical-Reasoning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from xtools-at/SmolLM3-3B-Medical-Reasoning: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/xtools-at/SmolLM3-3B-Medical-Reasoning/resolve/main/tokenizer.json
- Command line
-
hf download hf://xtools-at/SmolLM3-3B-Medical-Reasoning/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/xtools-at/SmolLM3-3B-Medical-Reasoning/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- e73f10c7dceb1adb001f2a44e75c1e2c06c99c818a9525d8bf6fe2b9eb43403b
- Size of remote file:
- 17.2 MB
- SHA256:
- 7b6a500b662a34eb3f0374db856ba4ad7de4c81040571d78dc0d357238930005
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.