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:
- 90fd6c19e8e1d55f7fc6f8aaae2f2a950b5e5c753fdd2b37ab38d7a0b1765dae
- Size of remote file:
- 1.5 MB
- SHA256:
- 0fb90bfa35244d26f0065d1fcd0b5becc3da3d44d616a7e2aacaf6320b9fa2d0
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