Instructions to use sharecreative/spam_classifier_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sharecreative/spam_classifier_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sharecreative/spam_classifier_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sharecreative/spam_classifier_v1") model = AutoModelForSequenceClassification.from_pretrained("sharecreative/spam_classifier_v1") - Notebooks
- Google Colab
- Kaggle
Upload RobertaForSequenceClassification
Browse files- config.json +4 -0
config.json
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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": "not_spam",
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"1": "spam"
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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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