Instructions to use vvn/summarizer_BART_aml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vvn/summarizer_BART_aml with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vvn/summarizer_BART_aml") model = AutoModelForSeq2SeqLM.from_pretrained("vvn/summarizer_BART_aml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe1fe28134345246ea194d35abbcbd17fa1dfaf136527c4b85d150eb63311cad
- Size of remote file:
- 1.63 GB
- SHA256:
- 2cee1fe33ae5d78f94f107014d67b26657e08787270c8435b65e154dc8427bde
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.