Instructions to use CodeAtCMU/gemma-3-4b-pt-GenerativePerturbations_full_sft_code_data_120K_flowchart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeAtCMU/gemma-3-4b-pt-GenerativePerturbations_full_sft_code_data_120K_flowchart with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CodeAtCMU/gemma-3-4b-pt-GenerativePerturbations_full_sft_code_data_120K_flowchart", dtype="auto") - Notebooks
- Google Colab
- Kaggle
gemma-3-4b-pt-GenerativePerturbations_full_sft_code_data_120K_flowchart / model-00003-of-00004.safetensors
- Xet hash:
- 78ae9ba4ae015447fd1563bba27a2f7b7ab18ca5c0ec8e121f366792b2a9e5e1
- Size of remote file:
- 4.91 GB
- SHA256:
- a2b3e87f09a56c0451ff2f93cb3facd5c4080092fdad637e59f12de819c55c45
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.