Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use PuxAI/PII-Binary-Filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PuxAI/PII-Binary-Filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PuxAI/PII-Binary-Filter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PuxAI/PII-Binary-Filter") model = AutoModelForSequenceClassification.from_pretrained("PuxAI/PII-Binary-Filter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3aef0cc066d933683430cb43dd03fe5d36555af9cac23d54a026908afe03f8b9
- Size of remote file:
- 541 MB
- SHA256:
- 35791f588ff1e97018a2fdf9bc33efe5800b6c77e31fd7cfc1e8cb708cb9a500
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