Instructions to use mpalaval/assignment2_attempt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/assignment2_attempt5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mpalaval/assignment2_attempt5") model = AutoModelForSeq2SeqLM.from_pretrained("mpalaval/assignment2_attempt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc6c33bf0827d98518ffbc31c1445117bc6369771549ebb2a7c549515d162eb7
- Size of remote file:
- 4.73 kB
- SHA256:
- 47b3b3763dccdd5685232ce23f99b86fa9b4137f72a4add53be29e8ffebff111
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.