Instructions to use J-MADRAL/P-MADRAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use J-MADRAL/P-MADRAL with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("J-MADRAL/P-MADRAL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "aen_module": "MadralAEN", | |
| "afn_module": "AspectsGatingAFN", | |
| "architectures": [ | |
| "BiEncoderModel" | |
| ], | |
| "aspects_size": [ | |
| 5171, | |
| 58, | |
| 444, | |
| 2294, | |
| 5241, | |
| 2208, | |
| 4, | |
| 13 | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "encoder_module": "BERT", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "num_aspects": 8, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_module": "Aspects", | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.7.0", | |
| "type_vocab_size": 2, | |
| "vocab_size": 30522 | |
| } | |