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:
- cc252ad305ae08c00d6bdc8afc3aaa87d3bc60386e5f43ac39374930b21bf2bd
- Size of remote file:
- 4.86 kB
- SHA256:
- 4f6a66be23cbad9274df4135c95e8fa448a45fc9866588bbc7a8ec3dafa7fbdb
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