Token Classification
GLiNER
PyTorch
multilingual
bert
Inference Endpoints
Gliner_haystack / config.json
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{
"model_type": "bert",
"size_sup": -1,
"max_types": 25,
"shuffle_types": true,
"random_drop": true,
"max_neg_type_ratio": 1,
"max_len": 384,
"lr_encoder": "1e-5",
"lr_others": "5e-5",
"num_steps": 30000,
"warmup_ratio": 3000,
"train_batch_size": 8,
"eval_every": 5000,
"max_width": 12,
"model_name": "microsoft/mdeberta-v3-base",
"fine_tune": true,
"subtoken_pooling": "first",
"hidden_size": 768,
"num_attention_heads": 12,
"num_hidden_layers": 12,
"intermediate_size": 3072,
"span_mode": "markerV0",
"dropout": 0.4,
"name": "correct"
}