Text Classification
Transformers
Safetensors
English
deberta-v2
digital-humanities
historical-text
ai-text-detection
deberta-v3
chronologic
Eval Results (legacy)
text-embeddings-inference
Instructions to use chronologic/chronologic-authenticity-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chronologic/chronologic-authenticity-deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chronologic/chronologic-authenticity-deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chronologic/chronologic-authenticity-deberta") model = AutoModelForSequenceClassification.from_pretrained("chronologic/chronologic-authenticity-deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Human-readable id2label/label2id
Browse files- config.json +2 -2
config.json
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@@ -8,12 +8,12 @@
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"
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},
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"layer_norm_eps": 1e-07,
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"legacy": true,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "synthetic"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"synthetic": 0
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},
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"layer_norm_eps": 1e-07,
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"legacy": true,
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