Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use msperka/dictabert_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msperka/dictabert_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="msperka/dictabert_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("msperka/dictabert_ner") model = AutoModelForTokenClassification.from_pretrained("msperka/dictabert_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c4bc01be0e093a4678383c54a01f12106051abb2f2506a73d85685acf6049e6
- Size of remote file:
- 7.77 kB
- SHA256:
- d338cd27b32fb200868bba9a3db4efc9462d3e909e7ee86c5cc231d35ffe60a0
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