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
Add model with label mapping
Browse files- config.json +57 -57
config.json
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{
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"_name_or_path": "./
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"architectures": [
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"ModernBertForSequenceClassification"
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],
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"hidden_activation": "gelu",
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"hidden_size": 768,
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"id2label": {
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},
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 1152,
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"label2id": {
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"layer_norm_eps": 1e-05,
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"local_attention": 128,
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"_name_or_path": "./modernbert-base-go-emotions",
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"architectures": [
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"ModernBertForSequenceClassification"
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],
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"hidden_activation": "gelu",
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"hidden_size": 768,
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"id2label": {
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"0": "admiration",
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"1": "amusement",
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"2": "anger",
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"3": "annoyance",
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"4": "approval",
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"5": "caring",
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"6": "confusion",
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"7": "curiosity",
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"8": "desire",
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"9": "disappointment",
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"10": "disapproval",
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"11": "disgust",
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"12": "embarrassment",
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"13": "excitement",
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"14": "fear",
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"15": "gratitude",
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"16": "grief",
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"17": "joy",
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"18": "love",
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"19": "nervousness",
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"20": "optimism",
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"21": "pride",
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"22": "realization",
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"23": "relief",
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"24": "remorse",
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"25": "sadness",
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"26": "surprise",
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"27": "neutral"
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},
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 1152,
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"label2id": {
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"admiration": 0,
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"amusement": 1,
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"anger": 2,
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"annoyance": 3,
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"approval": 4,
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"caring": 5,
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"confusion": 6,
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"curiosity": 7,
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"desire": 8,
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"disappointment": 9,
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"disapproval": 10,
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"disgust": 11,
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"embarrassment": 12,
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"excitement": 13,
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"fear": 14,
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"gratitude": 15,
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"grief": 16,
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"joy": 17,
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"love": 18,
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"nervousness": 19,
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"neutral": 27,
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"optimism": 20,
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"pride": 21,
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"realization": 22,
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"relief": 23,
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"remorse": 24,
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"sadness": 25,
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"surprise": 26
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},
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"layer_norm_eps": 1e-05,
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"local_attention": 128,
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