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:
- 4a650d2a072155234e67fa322023cff949383ff27828597da61ab7a70e66de65
- Size of remote file:
- 431 MB
- SHA256:
- 4c1555df63fbfc9a68284f288245e1bad452a0afc01f48ceb1b85d1c40ed2dcb
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