Instructions to use tesemnikov-av/rubert-ner-toxicity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tesemnikov-av/rubert-ner-toxicity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tesemnikov-av/rubert-ner-toxicity")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tesemnikov-av/rubert-ner-toxicity") model = AutoModelForTokenClassification.from_pretrained("tesemnikov-av/rubert-ner-toxicity") - Notebooks
- Google Colab
- Kaggle
NER Toxic models
Fine-tuning cointegrated/rubert-tiny-toxicity model on data from toxic_dataset_ner
language: RU
!pip install transformers > /dev/null
from transformers import (
AutoModelForTokenClassification,
AutoTokenizer,
pipeline
)
model = AutoModelForTokenClassification.from_pretrained('tesemnikov-av/rubert-ner-toxicity')
tokenizer = AutoTokenizer.from_pretrained('tesemnikov-av/rubert-ner-toxicity')
pipe = pipeline(model=model, tokenizer=tokenizer, task='ner', aggregation_strategy='average')
text = "Они охриневшие там все придурки!!"
print(text)
print(pipe(text))
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