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:
- 3467d304dcea9f42a19978d3dd898f0410c3833f4cb32d9fc9e0401c48ebd8c1
- Size of remote file:
- 4.73 kB
- SHA256:
- c4341714fc733449bd7d03f0ba8d845e1db9b9eae9d0fa0387e1aa16f1da3ec7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.