Instructions to use JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0/resolve/main/training_args.bin
- Command line
-
hf download hf://JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/JackS9/SmolLM2-1.7B-Instruct-thinking-function_calling-V0/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- 15d33781207a74f091bdb7eeb4dd499bac00b058e6db31b1fba591c2f5072906
- Size of remote file:
- 5.69 kB
- SHA256:
- 9b80254ea0442fe25c6c4522d969862428689059d5f553215074561029ea1fd2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.