Transformers
Safetensors
English
t5
text2text-generation
text-summarization
Generated from Trainer
text-generation-inference
Instructions to use agentlans/text-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agentlans/text-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("agentlans/text-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("agentlans/text-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ec12b1e184e25a67ee574dd63f1473c90ca159892428eca9e6a9c7a3ac70bfd
- Size of remote file:
- 5.43 kB
- SHA256:
- 84408ea749da0de549ece7f75903273bf7166244fa3b6512c77bcf9a51841624
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.