Instructions to use Saravananofficial/Text_Summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saravananofficial/Text_Summarizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Saravananofficial/Text_Summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("Saravananofficial/Text_Summarizer") - Notebooks
- Google Colab
- Kaggle
Commit ·
5c6f564
1
Parent(s): cb56a86
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,8 +7,8 @@ license: apache-2.0
|
|
| 7 |
An Abstractive text summarizer trained using lstm based sequence to sequence model with attention mechanisim. The attention model is used for generating each word of the summary conditioned on the input sentence.
|
| 8 |
|
| 9 |
- Used CNN_DailyMail dataset.
|
| 10 |
-
- Code
|
| 11 |
-
[](https://www.youtube.com/watch?v=LFZBA99NOpU)
|
| 12 |
|
| 13 |
### Training Model Overview
|
| 14 |
|
|
|
|
| 26 |
|
| 27 |
## Deployments:
|
| 28 |
|
| 29 |
+
- 🫶 https://text-summariser-v1.herokuapp.com/
|