Instructions to use SushantGautam/t5-Summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/t5-Summarizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SushantGautam/t5-Summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("SushantGautam/t5-Summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc42b3487f503c57b2a3a21a50aaf2a8f555693dc4aff12575e75d16c08e9e40
- Size of remote file:
- 5.11 kB
- SHA256:
- 2b8b164b8b1508b764771f279ee0f44da28fd71ffb2d56136df0a9c34520163c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.