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:
- b957eb28b60ec7f315fefc93ac5af629c8bb7f3c262667dd5a012eae53e57dbf
- Size of remote file:
- 735 MB
- SHA256:
- f7c6fdaa2c8139cf8edd9b04d6928b148edfd6f1531847632c4b4f6fc0d6703a
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