Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use pranay-j/bert-base-uncased-google-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pranay-j/bert-base-uncased-google-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pranay-j/bert-base-uncased-google-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pranay-j/bert-base-uncased-google-boolq") model = AutoModelForSequenceClassification.from_pretrained("pranay-j/bert-base-uncased-google-boolq") - Notebooks
- Google Colab
- Kaggle
Updated labelid
Browse files- config.json +2 -2
config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "True"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"True": 0
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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