Instructions to use SterlingWork/sdg-classifier-multilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SterlingWork/sdg-classifier-multilabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SterlingWork/sdg-classifier-multilabel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SterlingWork/sdg-classifier-multilabel") model = AutoModelForSequenceClassification.from_pretrained("SterlingWork/sdg-classifier-multilabel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,886 Bytes
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"architectures": [
"ModernBertForSequenceClassification"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 50281,
"classifier_activation": "gelu",
"classifier_bias": false,
"classifier_dropout": 0.0,
"classifier_pooling": "mean",
"cls_token_id": 50281,
"decoder_bias": true,
"deterministic_flash_attn": false,
"dtype": "float32",
"embedding_dropout": 0.0,
"eos_token_id": 50282,
"global_attn_every_n_layers": 3,
"global_rope_theta": 160000.0,
"gradient_checkpointing": false,
"hidden_activation": "gelu",
"hidden_size": 768,
"id2label": {
"0": "SDG 1",
"1": "SDG 2",
"2": "SDG 3",
"3": "SDG 4",
"4": "SDG 5",
"5": "SDG 6",
"6": "SDG 7",
"7": "SDG 8",
"8": "SDG 9",
"9": "SDG 10",
"10": "SDG 11",
"11": "SDG 12",
"12": "SDG 13",
"13": "SDG 14",
"14": "SDG 15",
"15": "SDG 16"
},
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"intermediate_size": 1152,
"label2id": {
"SDG 1": 0,
"SDG 10": 9,
"SDG 11": 10,
"SDG 12": 11,
"SDG 13": 12,
"SDG 14": 13,
"SDG 15": 14,
"SDG 16": 15,
"SDG 2": 1,
"SDG 3": 2,
"SDG 4": 3,
"SDG 5": 4,
"SDG 6": 5,
"SDG 7": 6,
"SDG 8": 7,
"SDG 9": 8
},
"layer_norm_eps": 1e-05,
"local_attention": 128,
"local_rope_theta": 10000.0,
"max_position_embeddings": 8192,
"mlp_bias": false,
"mlp_dropout": 0.0,
"model_type": "modernbert",
"norm_bias": false,
"norm_eps": 1e-05,
"num_attention_heads": 12,
"num_hidden_layers": 22,
"pad_token_id": 50283,
"position_embedding_type": "absolute",
"problem_type": "multi_label_classification",
"repad_logits_with_grad": false,
"sep_token_id": 50282,
"sparse_pred_ignore_index": -100,
"sparse_prediction": false,
"transformers_version": "4.57.3",
"vocab_size": 50368
}
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