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
Update README.md
Browse files
README.md
CHANGED
|
@@ -43,7 +43,7 @@ base_model:
|
|
| 43 |
|
| 44 |
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**.
|
| 45 |
|
| 46 |
-
|
| 47 |
|
| 48 |
> [!NOTE]
|
| 49 |
> 💻 **Demos**: Try this fine-tuned model running in a CPU-only Hugging Face space:
|
|
|
|
| 43 |
|
| 44 |
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**.
|
| 45 |
|
| 46 |
+
|
| 47 |
|
| 48 |
> [!NOTE]
|
| 49 |
> 💻 **Demos**: Try this fine-tuned model running in a CPU-only Hugging Face space:
|