Text Classification
Transformers
ONNX
Safetensors
English
modernbert
agents
context-management
topic-shift
cross-encoder
text-embeddings-inference
Instructions to use danielrosehill/Agent-Task-Break-Detector-ModernBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielrosehill/Agent-Task-Break-Detector-ModernBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielrosehill/Agent-Task-Break-Detector-ModernBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielrosehill/Agent-Task-Break-Detector-ModernBERT") model = AutoModelForSequenceClassification.from_pretrained("danielrosehill/Agent-Task-Break-Detector-ModernBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from danielrosehill/Agent-Task-Break-Detector-ModernBERT: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/danielrosehill/Agent-Task-Break-Detector-ModernBERT/resolve/main/tokenizer.json
- Command line
-
hf download hf://danielrosehill/Agent-Task-Break-Detector-ModernBERT/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/danielrosehill/Agent-Task-Break-Detector-ModernBERT/resolve/main/tokenizer.json
3.58 MB
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