Text Classification
Transformers
PyTorch
Safetensors
English
roberta
hate-speech
text-embeddings-inference
Instructions to use classla/roberta-base-frenk-hate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/roberta-base-frenk-hate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classla/roberta-base-frenk-hate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classla/roberta-base-frenk-hate") model = AutoModelForSequenceClassification.from_pretrained("classla/roberta-base-frenk-hate") - Notebooks
- Google Colab
- Kaggle
Added id2label field in config
Browse files- config.json +4 -0
config.json
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@@ -10,6 +10,10 @@
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"hidden_act": "gelu",
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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": "Acceptable",
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"1": "Offensive"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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