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
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README.md
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## Model description
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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## Training procedure
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## Model description
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PretoTM NER is a model developed to recognize relevant entities associated with treatment-related findings in preclinical toxicology.
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## Training and evaluation data
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The model was trained on [javicorvi/pretoxtm-dataset](https://huggingface.co/datasets/javicorvi/pretoxtm-dataset).
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The dataset is divided in train, validation and test.
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## Training procedure
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