Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-xl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-xl") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-xl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
db69d5e
1
Parent(s): 63dfd57
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,8 +9,7 @@ tags:
|
|
| 9 |
license: apache-2.0
|
| 10 |
---
|
| 11 |
|
| 12 |
-
# T5-Efficient-XL
|
| 13 |
-
### *One of T5's Deep-Narrow checkpoints*
|
| 14 |
|
| 15 |
T5-Efficient-XL is a variation of the original [T5-3B](https://huggingface.co/t5-3b) checkpoint and follows the [T5 model architecture](https://huggingface.co/docs/transformers/model_doc/t5).
|
| 16 |
It is a *pretrained-only* checkpoint and was released with the
|
|
|
|
| 9 |
license: apache-2.0
|
| 10 |
---
|
| 11 |
|
| 12 |
+
# T5-Efficient-XL (Deep-Narrow version)
|
|
|
|
| 13 |
|
| 14 |
T5-Efficient-XL is a variation of the original [T5-3B](https://huggingface.co/t5-3b) checkpoint and follows the [T5 model architecture](https://huggingface.co/docs/transformers/model_doc/t5).
|
| 15 |
It is a *pretrained-only* checkpoint and was released with the
|