Text Classification
Transformers
Safetensors
xlm-roberta
ner
on-device
privacy
flowx
openner
cross
de-identification
text-embeddings-inference
Instructions to use flowxai/privacyfilter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/privacyfilter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flowxai/privacyfilter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/privacyfilter") model = AutoModelForSequenceClassification.from_pretrained("flowxai/privacyfilter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 223 Bytes
0ae0878 | 1 2 3 4 5 6 7 8 9 10 | {
"test_loss": 1.3209909411671106e-05,
"test_accuracy": 1.0,
"test_macro_f1": 1.0,
"test_f1": 1.0,
"test_runtime": 2.0996,
"test_samples_per_second": 1905.092,
"test_steps_per_second": 59.534,
"epoch": 3.0
} |