Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use machinelearningzuu/lesson-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use machinelearningzuu/lesson-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("machinelearningzuu/lesson-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("machinelearningzuu/lesson-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c03c8d75f43237c3671e7680945795563c62cf0ddf96b8231805a09f8bc5240
- Size of remote file:
- 242 MB
- SHA256:
- e959ca18bc865157855324ea705b1bf013fd1ccb30a497be656b2c94f030debc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.