Instructions to use Shushant/nepaliBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shushant/nepaliBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Shushant/nepaliBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Shushant/nepaliBERT") model = AutoModelForMaskedLM.from_pretrained("Shushant/nepaliBERT") - Notebooks
- Google Colab
- Kaggle
Fix: Add newline to fix SyntaxError in example code
#4
by anon-repair-bot - opened
README.md
CHANGED
|
@@ -42,7 +42,8 @@ model = AutoModelForMaskedLM.from_pretrained("Shushant/nepaliBERT")
|
|
| 42 |
from transformers import pipeline
|
| 43 |
|
| 44 |
fill_mask = pipeline( "fill-mask", model=model, tokenizer=tokenizer, )
|
| 45 |
-
from pprint import pprint
|
|
|
|
| 46 |
```
|
| 47 |
|
| 48 |
## Data Description
|
|
|
|
| 42 |
from transformers import pipeline
|
| 43 |
|
| 44 |
fill_mask = pipeline( "fill-mask", model=model, tokenizer=tokenizer, )
|
| 45 |
+
from pprint import pprint
|
| 46 |
+
pprint(fill_mask(f"तिमीलाई कस्तो {tokenizer.mask_token}."))
|
| 47 |
```
|
| 48 |
|
| 49 |
## Data Description
|