Text2Text Generation
Transformers
PyTorch
Oriya
Hindi
English
mt5
india language
Inference Endpoints
odia-t5-base / config.json
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odia t5 base model.
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{
"_name_or_path": "google/mt5-small",
"architectures": [
"MT5ForConditionalGeneration"
],
"d_ff": 1024,
"d_kv": 64,
"d_model": 512,
"decoder_start_token_id": 0,
"dropout_rate": 0.1,
"eos_token_id": 1,
"feed_forward_proj": "gated-gelu",
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"layer_norm_epsilon": 1e-06,
"model_type": "mt5",
"num_decoder_layers": 8,
"num_heads": 6,
"num_layers": 8,
"pad_token_id": 0,
"relative_attention_num_buckets": 32,
"tie_word_embeddings": false,
"tokenizer_class": "T5Tokenizer",
"torch_dtype": "float32",
"transformers_version": "4.16.2",
"use_cache": true,
"vocab_size": 250112
}