Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
chemistry
biology
medical
Instructions to use javicorvi/pretoxtm-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use javicorvi/pretoxtm-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="javicorvi/pretoxtm-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("javicorvi/pretoxtm-ner") model = AutoModelForTokenClassification.from_pretrained("javicorvi/pretoxtm-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44049e74be7ad9bea9fcda1231e4e0b826c4601fe81d0e9562c9334f23ebe23e
- Size of remote file:
- 431 MB
- SHA256:
- 3310998b3007e3241d50263db893b2075c1a6b9d2163cd275f90a5c2197a1552
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