Transformers
PyTorch
TensorFlow
English
t5
text2text-generation
t5-lm-adapt
text-generation-inference
Instructions to use google/t5-base-lm-adapt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-base-lm-adapt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-base-lm-adapt") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-base-lm-adapt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33d5190d44f6b354e25cffc655b6e6550a8d785670c1169f86319584989a3463
- Size of remote file:
- 990 MB
- SHA256:
- 00ebc4e1a7366f129ee2491d85d5b1a10b27c0303c8514e3fbefd36b01acf607
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.