Instructions to use ayjays132/EnhancerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayjays132/EnhancerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ayjays132/EnhancerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ayjays132/EnhancerModel") model = AutoModel.from_pretrained("ayjays132/EnhancerModel") - Notebooks
- Google Colab
- Kaggle
File size: 4,212 Bytes
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"_name_or_path": "ayjays132/CustomGPT2Conversational",
"activation_function": "gelu_new",
"advanced_model_options": {
"contextual_embeddings": {
"approaches": [
"contextual_attention_mechanisms",
"semantic_embedding_regularization"
],
"enable": true
},
"dynamic_adaptation": {
"enable": true,
"techniques": [
"adaptive_layer_dropping",
"dynamic_context_window"
]
},
"innovative_neuron_growth": {
"enable": true,
"strategies": [
"selective_neuron_pruning",
"progressive_neuron_expansion"
]
},
"memory_optimization": {
"enable": true,
"methods": [
"gradient_checkpointing",
"memory-efficient_attention"
]
},
"meta_learning": {
"approaches": [
"meta_learning_rate_adjustment",
"online_adaptation"
],
"enable": true
},
"secret_advanced_options": {
"adaptive_token_embedding": {
"enable": true,
"strategies": [
"dynamic_embedding_resizing",
"contextual_embedding_scaling"
]
},
"future_context_prediction": {
"enable": true,
"techniques": [
"lookahead_context_integration",
"predictive_attention_mechanisms"
]
},
"multi_modal_integration": {
"enable": true,
"methods": [
"text_image_alignment",
"cross_modal_attention"
]
}
}
},
"activation_dropout": 0.1,
"activation_function": "gelu",
"add_bias_logits": false,
"add_final_layer_norm": false,
"architectures": [
"BartModel"
],
"attention_dropout": 0.1,
"bos_token_id": 0,
"classif_dropout": 0.1,
"classifier_dropout": 0.0,
"d_model": 1024,
"decoder_attention_heads": 16,
"decoder_ffn_dim": 4096,
"decoder_layerdrop": 0.0,
"decoder_layers": 12,
"decoder_start_token_id": 2,
"dropout": 0.1,
"early_stopping": true,
"encoder_attention_heads": 16,
"encoder_ffn_dim": 4096,
"encoder_layerdrop": 0.0,
"encoder_layers": 12,
"eos_token_id": 2,
"forced_eos_token_id": 2,
"forced_bos_token_id": 0,
"gradient_checkpointing": false,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1",
"2": "LABEL_2"
},
"init_std": 0.02,
"is_encoder_decoder": true,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1,
"LABEL_2": 2
},
"max_position_embeddings": 1024,
"model_type": "bart",
"no_repeat_ngram_size": 3,
"normalize_before": false,
"num_beams": 4,
"num_hidden_layers": 12,
"pad_token_id": 1,
"scale_embedding": false,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.1,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"sep_token_id": 50267,
"special_tokens": {
"additional_special_tokens": [
"<greeting>",
"<farewell>",
"<thank>",
"<apology>"
],
"bos_token": "<bos>",
"cls_token": "<cls>",
"eos_token": "<eos>",
"mask_token": "<mask>",
"pad_token": "<pad>",
"sep_token": "<sep>",
"unk_token": "<unk>"
},
"state_shape": null,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"target_q_model": null,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"early_stopping": true,
"length_penalty": 1.0,
"max_length": 2048,
"min_length": 64,
"no_repeat_ngram_size": 2,
"num_beams": 8,
"num_return_sequences": 3,
"repetition_penalty": 1.2,
"temperature": 0.9,
"top_k": 50,
"top_p": 0.95
},
"summarization": {
"length_penalty": 1.0,
"max_length": 128,
"min_length": 12,
"num_beams": 4
},
"summarization_cnn": {
"length_penalty": 2.0,
"max_length": 142,
"min_length": 56,
"num_beams": 4
},
"summarization_xsum": {
"length_penalty": 1.0,
"max_length": 62,
"min_length": 11,
"num_beams": 6
}
},
"torch_dtype": "float32",
"transformers_version": "4.7.0.dev0",
"use_cache": true,
"vocab_size": 50265
}
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