Zero-Shot Classification
Transformers
PyTorch
102 languages
T5
classification
information-extraction
zero-shot
Inference Endpoints
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{
"architectures": [
"T5ForZeroShotClassification"
],
"classifier_dropout": 0.0,
"d_ff": 2048,
"d_kv": 64,
"d_model": 768,
"decoder_start_token_id": 0,
"dense_act_fn": "gelu_new",
"dropout_rate": 0.1,
"encoder_attention_type": "block",
"eos_token_id": 1,
"feed_forward_proj": "gated-gelu",
"global_block_size": 128,
"id2label": {
"0": "contradiction",
"1": "entailment",
"2": "neutral"
},
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"is_gated_act": true,
"label2id": {
"contradiction": 0,
"entailment": 1,
"neutral": 2
},
"layer_norm_epsilon": 1e-06,
"loss_type": "cross_entropy",
"model_type": "T5",
"naive_attention": true,
"num_decoder_layers": 12,
"num_heads": 12,
"num_layers": 12,
"output_past": true,
"pad_token_id": 0,
"positional_embedding_type": "relative",
"problem_type": "single_label_classification",
"relative_attention_max_distance": 128,
"relative_attention_num_buckets": 32,
"residuals": "pre",
"sliding_window": 128,
"tie_word_embeddings": false,
"tokenizer_class": "T5Tokenizer",
"torch_dtype": "float32",
"transformers_version": "4.33.0.dev0",
"use_cache": true,
"vocab_size": 250112
}