Instructions to use UsernameNLP/calculator_model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UsernameNLP/calculator_model_test with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("UsernameNLP/calculator_model_test") model = AutoModelForSeq2SeqLM.from_pretrained("UsernameNLP/calculator_model_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17e596fb86d9a21c743059b4467990ae644f5705463d415cfe870f3330ad1539
- Size of remote file:
- 5.11 kB
- SHA256:
- fe3f7e0fa73cedb66b8fc7cd8d15f873d0b181c1bbf84b7d816a974ee59f0466
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.