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:
- 494a85c14587aa2d77eb34dd17390e1942cfb21176c17109869da14e541af2ee
- Size of remote file:
- 5.53 kB
- SHA256:
- 63530312253fffc1a5bafbaf6f69ab8ee0e286139e8ba0b2b8987bf39370df05
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