Instructions to use errchh/SmolLM2-reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use errchh/SmolLM2-reasoning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("errchh/SmolLM2-reasoning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from errchh/SmolLM2-reasoning: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/errchh/SmolLM2-reasoning/resolve/main/training_args.bin
- Command line
-
hf download hf://errchh/SmolLM2-reasoning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/errchh/SmolLM2-reasoning/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- b96deb72b0499501745b72f801503e3f9872ba773f967cf03c99c483d232a067
- Size of remote file:
- 5.62 kB
- SHA256:
- 282eb387bb4b8309b3d51d6f279855030fddad57d89836e2c198c4cc0857a02d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.