Instructions to use SMG0/Model3_Marabertv2_T2_WOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SMG0/Model3_Marabertv2_T2_WOS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SMG0/Model3_Marabertv2_T2_WOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SMG0/Model3_Marabertv2_T2_WOS") model = AutoModelForSequenceClassification.from_pretrained("SMG0/Model3_Marabertv2_T2_WOS") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "UBC-NLP/MARBERTv2", | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "RH:ISLAM", | |
| "1": "RH:Judaism", | |
| "2": "RH:Christianity", | |
| "3": "UD_RH", | |
| "4": "EH:ARAB", | |
| "5": "EH:African", | |
| "6": "UD_EH", | |
| "7": "NH:Iranian", | |
| "8": "NH:Israeli", | |
| "9": "NH:Saudi", | |
| "10": "NH:Turkish", | |
| "11": "NH:Qatari", | |
| "12": "NH:American", | |
| "13": "UD_NH", | |
| "14": "GH:Females", | |
| "15": "GH:Males", | |
| "16": "UD_GH" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "EH:ARAB": 4, | |
| "EH:African": 5, | |
| "GH:Females": 14, | |
| "GH:Males": 15, | |
| "NH:American": 12, | |
| "NH:Iranian": 7, | |
| "NH:Israeli": 8, | |
| "NH:Qatari": 11, | |
| "NH:Saudi": 9, | |
| "NH:Turkish": 10, | |
| "RH:Christianity": 2, | |
| "RH:ISLAM": 0, | |
| "RH:Judaism": 1, | |
| "UD_EH": 6, | |
| "UD_GH": 16, | |
| "UD_NH": 13, | |
| "UD_RH": 3 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "problem_type": "multi_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.31.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 100000 | |
| } | |