Instructions to use AI4BPM/process_for_optimizing_a_process_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4BPM/process_for_optimizing_a_process_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AI4BPM/process_for_optimizing_a_process_model") model = AutoModelForSeq2SeqLM.from_pretrained("AI4BPM/process_for_optimizing_a_process_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35f755f2e3385c151fb0875a5ac807736b9968f6c22576ff9efd55852e389ebe
- Size of remote file:
- 242 MB
- SHA256:
- e0dd38c7bccef0b5d41923cb749defd9adc236a51be6dca2ad87b3bd47135ef2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.