Transformers
TensorBoard
Safetensors
Vietnamese
mbart
text2text-generation
code
Eval Results (legacy)
Instructions to use minhbui/spell_correction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minhbui/spell_correction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("minhbui/spell_correction") model = AutoModelForSeq2SeqLM.from_pretrained("minhbui/spell_correction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,11 +26,4 @@ model-index:
|
|
| 26 |
- name: val_loss
|
| 27 |
type: val_loss
|
| 28 |
value: 0.1414
|
| 29 |
-
widget:
|
| 30 |
-
- text: "H么m ny tr峄漣 d岷筽 qu谩 !"
|
| 31 |
-
output:
|
| 32 |
-
- label: POSITIVE
|
| 33 |
-
score: 0.8
|
| 34 |
-
- label: NEGATIVE
|
| 35 |
-
score: 0.2
|
| 36 |
---
|
|
|
|
| 26 |
- name: val_loss
|
| 27 |
type: val_loss
|
| 28 |
value: 0.1414
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 29 |
---
|