Text Classification
Transformers
Safetensors
Dutch
bert
BERTje
Filtering
Data Cleaning
text-embeddings-inference
Instructions to use Kalamazooter/DutchDatasetCleaner_Bertje with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kalamazooter/DutchDatasetCleaner_Bertje with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kalamazooter/DutchDatasetCleaner_Bertje")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kalamazooter/DutchDatasetCleaner_Bertje") model = AutoModelForSequenceClassification.from_pretrained("Kalamazooter/DutchDatasetCleaner_Bertje", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model was created with the intention of easily being able to filter large synthetic datasets in the Dutch language.
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It was mostly trained to pick out strings with a lot of repitition, weird grammar or refusals specifically, returning either ["Correct","Error","Refusal"]
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THIS IS NOT THE FINAL VERSION, MORE ITERATIONS IN THE NEXT FEW WEEKS
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## How to use
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```python
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This model was created with the intention of easily being able to filter large synthetic datasets in the Dutch language.
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It was mostly trained to pick out strings with a lot of repitition, weird grammar or refusals specifically, returning either ["Correct","Error","Refusal"]
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## How to use
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```python
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