Token Classification
Transformers
PyTorch
Safetensors
German
xlm-roberta
legal
tax law
relation extraction
entity extraction
Instructions to use danielsteinigen/KeyFiTax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsteinigen/KeyFiTax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="danielsteinigen/KeyFiTax")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("danielsteinigen/KeyFiTax") model = AutoModelForTokenClassification.from_pretrained("danielsteinigen/KeyFiTax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- tax law
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- relation extraction
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- entity extraction
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---
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# Model Card for Model ID
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- **Demo:** https://huggingface.co/spaces/danielsteinigen/NLP-Legal-Texts
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## Uses
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```
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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from transformers import pipeline
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- tax law
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- relation extraction
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- entity extraction
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widget:
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- text: "testtext"
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example_title: "testtitle"
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---
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# Model Card for Model ID
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- **Demo:** https://huggingface.co/spaces/danielsteinigen/NLP-Legal-Texts
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## Uses
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```python
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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from transformers import pipeline
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