Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
genre
text-genre
text-embeddings-inference
Instructions to use classla/xlm-roberta-base-multilingual-text-genre-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/xlm-roberta-base-multilingual-text-genre-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classla/xlm-roberta-base-multilingual-text-genre-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier") model = AutoModelForSequenceClassification.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Taja Kuzman commited on
Commit ·
d31f5f4
1
Parent(s): 246b839
Update config.json
Browse files- config.json +9 -9
config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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0: "Other",
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1: "Information/Explanation",
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2: "News",
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3: "Instruction",
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4: "Opinion/Argumentation",
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5: "Forum",
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6: "Prose/Lyrical",
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7: "Legal",
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8: "Promotion"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "Other",
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"1": "Information/Explanation",
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"2": "News",
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"3": "Instruction",
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"4": "Opinion/Argumentation",
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"5": "Forum",
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"6": "Prose/Lyrical",
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"7": "Legal",
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"8": "Promotion"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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