Instructions to use transZ/ViT5-repara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/ViT5-repara with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transZ/ViT5-repara") model = AutoModelForSeq2SeqLM.from_pretrained("transZ/ViT5-repara") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2a7c0cb694f87a57f7936709bf28d60243814fc163179399038b04c8a07d393a
|
| 3 |
+
size 903834528
|