Instructions to use szymonpindur/herbert-onom-interjection-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use szymonpindur/herbert-onom-interjection-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="szymonpindur/herbert-onom-interjection-recognition")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("szymonpindur/herbert-onom-interjection-recognition") model = AutoModelForTokenClassification.from_pretrained("szymonpindur/herbert-onom-interjection-recognition") - Notebooks
- Google Colab
- Kaggle
Commit ·
fa0b593
1
Parent(s): 8c1050b
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,7 +14,7 @@ widget:
|
|
| 14 |
# HerBERT Polish Onomatopoeia Recognition
|
| 15 |
|
| 16 |
|
| 17 |
-
This model is a finetuned HerBERT large model (cased) on a sample of 800
|
| 18 |
The model allows to detect onomatopoeia in the form of interjections in any given text.
|
| 19 |
|
| 20 |
## Model Details
|
|
|
|
| 14 |
# HerBERT Polish Onomatopoeia Recognition
|
| 15 |
|
| 16 |
|
| 17 |
+
This model is a finetuned HerBERT large model (cased) on a sample of 800 sentences containing onomatopoeia from the Mirosław Bańko's Współczesny polski onomatopeikon: ikoniczność w języku (Bańko, 2008).
|
| 18 |
The model allows to detect onomatopoeia in the form of interjections in any given text.
|
| 19 |
|
| 20 |
## Model Details
|