Instructions to use Deepakvictor/tan-ta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deepakvictor/tan-ta with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Deepakvictor/tan-ta")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Deepakvictor/tan-ta") model = AutoModelForSeq2SeqLM.from_pretrained("Deepakvictor/tan-ta") - Notebooks
- Google Colab
- Kaggle
Update README.md
#2
by Hemanth-thunder - opened
README.md
CHANGED
|
@@ -2,7 +2,14 @@
|
|
| 2 |
license: creativeml-openrail-m
|
| 3 |
language:
|
| 4 |
- ta
|
|
|
|
| 5 |
pipeline_tag: translation
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 6 |
---
|
| 7 |
# Model Card for Deepakvictor/tan-ta
|
| 8 |
|
|
|
|
| 2 |
license: creativeml-openrail-m
|
| 3 |
language:
|
| 4 |
- ta
|
| 5 |
+
- en
|
| 6 |
pipeline_tag: translation
|
| 7 |
+
widget:
|
| 8 |
+
- text: Thalaivaru nirantharam
|
| 9 |
+
inference:
|
| 10 |
+
parameters:
|
| 11 |
+
src_lang : en
|
| 12 |
+
tgt_lang : ta
|
| 13 |
---
|
| 14 |
# Model Card for Deepakvictor/tan-ta
|
| 15 |
|