Text Classification
Transformers
Safetensors
English
modernbert
ai-text-detection
idea-provenance
text-embeddings-inference
Instructions to use rishanthrajendhran/IdeaLens-ModernBERT-L-RolesOnly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishanthrajendhran/IdeaLens-ModernBERT-L-RolesOnly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rishanthrajendhran/IdeaLens-ModernBERT-L-RolesOnly")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rishanthrajendhran/IdeaLens-ModernBERT-L-RolesOnly") model = AutoModelForSequenceClassification.from_pretrained("rishanthrajendhran/IdeaLens-ModernBERT-L-RolesOnly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Card: remove the access-request prompt (the repo is not gated)
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Card: cite the arXiv paper (2610.06778)
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Card: list the false-positive rates this model's thresholds cover
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License: CC BY-NC-SA 4.0
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Card: link the IdeaLens collection
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Card: quick start with the idealens package (classify, extract, score)
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Card: link the idealens package and GitHub repo; full card
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Rename the corpus IdeaLens-1M -> WildOutlines
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Add calibrated thresholds (IdeaLens-1M calibration split)
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initial upload
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model card
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initial commit
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