Instructions to use mpalaval/assignment2_attempt6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/assignment2_attempt6 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mpalaval/assignment2_attempt6") model = AutoModelForSeq2SeqLM.from_pretrained("mpalaval/assignment2_attempt6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efc4d3ddb67b17af8489acd9728773dc67a0ec8df9f23f35356c15992d296c79
- Size of remote file:
- 892 MB
- SHA256:
- d8085bcb4927602c15702d8a8ef15d25779de0611319efe3325b59f01d573d06
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.