Text Classification
Transformers
PyTorch
bert
Inference Endpoints
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{
  "architectures": [
    "BertForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 256,
  "initializer_range": 0.02,
  "intermediate_size": 1024,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 4,
  "num_hidden_layers": 4,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "transformers_version": "4.23.1",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 50099
}