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PPO-policy_v3

Text2Text Generation
Transformers
PyTorch
pegasus
Inference Endpoints
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SophieTr commited on
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1 Parent(s): b5e886f

add model

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Files changed (2) hide show
  1. config.json +124 -0
  2. pytorch_model.bin +3 -0
config.json ADDED
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+ {
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+ "_name_or_path": "QuickRead/pegasus-reddit-7e05",
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+ "activation_dropout": 0.1,
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+ "activation_function": "relu",
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+ "add_bias_logits": false,
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+ "add_final_layer_norm": true,
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+ "architectures": [
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+ "PegasusForConditionalGeneration"
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+ ],
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+ "attention_dropout": 0.1,
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+ "bos_token_id": 0,
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+ "classif_dropout": 0.0,
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+ "classifier_dropout": 0.0,
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+ "d_model": 1024,
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+ "decoder_attention_heads": 16,
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 16,
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+ "decoder_start_token_id": 0,
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+ "dropout": 0.1,
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+ "encoder_attention_heads": 16,
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+ "encoder_ffn_dim": 4096,
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+ "encoder_layerdrop": 0.0,
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+ "encoder_layers": 16,
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+ "eos_token_id": 1,
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+ "extra_pos_embeddings": 1,
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+ "force_bos_token_to_be_generated": false,
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+ "forced_eos_token_id": 1,
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "init_std": 0.02,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "length_penalty": 0.8,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024,
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+ "model_type": "pegasus",
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+ "normalize_before": true,
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+ "normalize_embedding": false,
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+ "num_beams": 8,
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+ "num_hidden_layers": 16,
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+ "pad_token_id": 0,
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+ "scale_embedding": true,
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+ "static_position_embeddings": true,
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+ "task_specific_params": {
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+ "summarization_aeslc": {
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+ "length_penalty": 0.6,
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+ "max_length": 32,
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+ "max_position_embeddings": 512
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+ },
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+ "summarization_arxiv": {
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+ "length_penalty": 0.8,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_big_patent": {
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+ "length_penalty": 0.7,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_billsum": {
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+ "length_penalty": 0.6,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_cnn_dailymail": {
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+ "length_penalty": 0.8,
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+ "max_length": 128,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_gigaword": {
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+ "length_penalty": 0.6,
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+ "max_length": 32,
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+ "max_position_embeddings": 128
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+ },
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+ "summarization_large": {
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+ "length_penalty": 0.8,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_multi_news": {
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+ "length_penalty": 0.8,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_newsroom": {
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+ "length_penalty": 0.8,
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+ "max_length": 128,
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+ "max_position_embeddings": 512
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+ },
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+ "summarization_pubmed": {
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+ "length_penalty": 0.8,
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+ "max_length": 256,
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+ "max_position_embeddings": 1024
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+ },
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+ "summarization_reddit_tifu": {
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+ "length_penalty": 0.6,
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+ "max_length": 128,
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+ "max_position_embeddings": 512
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+ },
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+ "summarization_wikihow": {
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+ "length_penalty": 0.6,
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+ "max_length": 256,
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+ "max_position_embeddings": 512
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+ },
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+ "summarization_xsum": {
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+ "length_penalty": 0.8,
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+ "max_length": 64,
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+ "max_position_embeddings": 512
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+ }
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.16.2",
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+ "use_cache": true,
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+ "vocab_size": 96103
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+ }
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