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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8280788ddefe6adc0e813627b697bf9d5713164eb5692ca36f4e8c633be5e72c
- Size of remote file:
- 5.84 kB
- SHA256:
- 99aafc4e1a0d44e1b959a8c9fc143d3b8e26fe06c92cec5aeda78e4fab722c59
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.