Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Axel578/flan_t5_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Axel578/flan_t5_summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Axel578/flan_t5_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Axel578/flan_t5_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c5cdbcbe000b4c1514b406cbb4b50560ebefe6582c01e113d68e204128e0175
- Size of remote file:
- 3.64 kB
- SHA256:
- 69c3ad11a747c7d2b632c627315f3a8394de84d6d0efd3d281256fbc9070ebfc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.