Instructions to use mpalaval/assignment2_attempt1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/assignment2_attempt1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mpalaval/assignment2_attempt1") model = AutoModelForSeq2SeqLM.from_pretrained("mpalaval/assignment2_attempt1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42ce23412d4a261651d82e04599438ee2ac6c753f2a7334e20b16c01ea391f2e
- Size of remote file:
- 892 MB
- SHA256:
- c6580449ae08b66c500be404006a8422283d0b8f76cc3a88072c207f6eb6e3d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.