Token Classification
Transformers
Safetensors
lfm2
liquid
lfm2.5
bidirectional
masked-lm
encoder
pii
ner
privacy
multilingual
custom_code
Instructions to use Omared1/LFM2.5-Encoder-350M-PII-Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Omared1/LFM2.5-Encoder-350M-PII-Detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Omared1/LFM2.5-Encoder-350M-PII-Detector", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Omared1/LFM2.5-Encoder-350M-PII-Detector", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("Omared1/LFM2.5-Encoder-350M-PII-Detector", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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<a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> •
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<a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> •
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<a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> •
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<a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a>
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# LFM2.5-Encoder-350-PII-Detector
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A full fine-tune of [LFM2.5-Encoder-350M](https://huggingface.co/LiquidAI/LFM2.5-Encoder-350M) with a token-classification head, covering **40 PII types** across **16 languages**.
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# LFM2.5-Encoder-350-PII-Detector
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A full fine-tune of [LFM2.5-Encoder-350M](https://huggingface.co/LiquidAI/LFM2.5-Encoder-350M) with a token-classification head, covering **40 PII types** across **16 languages**.
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