Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Kriyans/Bert-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kriyans/Bert-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kriyans/Bert-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Kriyans/Bert-NER") model = AutoModelForTokenClassification.from_pretrained("Kriyans/Bert-NER") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +2 -10
- pytorch_model.bin +2 -2
- training_args.bin +1 -1
config.json
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "
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"1": "B-corporation",
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"2": "I-corporation",
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"4": "I-person"
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"initializer_range": 0.02,
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"label2id": {
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"B-person": 3,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "B-PER"
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"initializer_range": 0.02,
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"label2id": {
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"B-PER": 0
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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pytorch_model.bin
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training_args.bin
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size 4027
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