Instructions to use Seonguk/textSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seonguk/textSummarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Seonguk/textSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("Seonguk/textSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete model_version0/pytorch_model.bin
Browse files
model_version0/pytorch_model.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:df960479b7f0905dd5ad86005e6efcc34dc08524cca8fb536743c97e768d5e64
|
| 3 |
-
size 495658703
|
|
|
|
|
|
|
|
|
|
|
|