Text Classification
Transformers
Safetensors
PyTorch
English
modernbert
ModernBERT
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use cirimus/modernbert-base-go-emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cirimus/modernbert-base-go-emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cirimus/modernbert-base-go-emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cirimus/modernbert-base-go-emotions") model = AutoModelForSequenceClassification.from_pretrained("cirimus/modernbert-base-go-emotions") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 3,157 Bytes
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"architectures": [
"ModernBertForSequenceClassification"
],
"attention_bias": false,
"attention_dropout": 0.05,
"bos_token_id": 50281,
"classifier_activation": "gelu",
"classifier_bias": false,
"classifier_dropout": 0.1,
"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,
"gradient_checkpointing": false,
"hidden_activation": "gelu",
"hidden_size": 768,
"id2label": {
"0": "admiration",
"1": "amusement",
"2": "anger",
"3": "annoyance",
"4": "approval",
"5": "caring",
"6": "confusion",
"7": "curiosity",
"8": "desire",
"9": "disappointment",
"10": "disapproval",
"11": "disgust",
"12": "embarrassment",
"13": "excitement",
"14": "fear",
"15": "gratitude",
"16": "grief",
"17": "joy",
"18": "love",
"19": "nervousness",
"20": "optimism",
"21": "pride",
"22": "realization",
"23": "relief",
"24": "remorse",
"25": "sadness",
"26": "surprise",
"27": "neutral"
},
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"intermediate_size": 1152,
"label2id": {
"admiration": 0,
"amusement": 1,
"anger": 2,
"annoyance": 3,
"approval": 4,
"caring": 5,
"confusion": 6,
"curiosity": 7,
"desire": 8,
"disappointment": 9,
"disapproval": 10,
"disgust": 11,
"embarrassment": 12,
"excitement": 13,
"fear": 14,
"gratitude": 15,
"grief": 16,
"joy": 17,
"love": 18,
"nervousness": 19,
"neutral": 27,
"optimism": 20,
"pride": 21,
"realization": 22,
"relief": 23,
"remorse": 24,
"sadness": 25,
"surprise": 26
},
"layer_norm_eps": 1e-05,
"layer_types": [
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention"
],
"local_attention": 128,
"max_position_embeddings": 8192,
"mlp_bias": false,
"mlp_dropout": 0.05,
"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",
"rope_parameters": {
"full_attention": {
"rope_theta": 160000.0,
"rope_type": "default"
},
"sliding_attention": {
"rope_theta": 10000.0,
"rope_type": "default"
}
},
"sep_token_id": 50282,
"sparse_pred_ignore_index": -100,
"sparse_prediction": false,
"tie_word_embeddings": true,
"transformers_version": "5.3.0",
"vocab_size": 50368
}
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