Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use dmargutierrez/distilbert-base-multilingual-cased-mapa_fine-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmargutierrez/distilbert-base-multilingual-cased-mapa_fine-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dmargutierrez/distilbert-base-multilingual-cased-mapa_fine-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dmargutierrez/distilbert-base-multilingual-cased-mapa_fine-ner") model = AutoModelForTokenClassification.from_pretrained("dmargutierrez/distilbert-base-multilingual-cased-mapa_fine-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76df38ebc6b997c485aaa7c0958f877c6cead4a97cd870a72ed683842ee12e48
- Size of remote file:
- 539 MB
- SHA256:
- 7649fe15569f5c4f7812c46b8ca9ca15587cf3ec9d218dfb256f6d0a5478abbe
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