Instructions to use datasetsANDmodels/request-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datasetsANDmodels/request-extraction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("datasetsANDmodels/request-extraction") model = AutoModelForSeq2SeqLM.from_pretrained("datasetsANDmodels/request-extraction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce5edd887edd533fdb854f6dd1da884080a33905ae0161547912b7fb5b311830
- Size of remote file:
- 2.42 MB
- SHA256:
- 04e7404608459e95fe67c3cf18a4c34369e15375a86e918d13644e5c7314699f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.