Feature Extraction
Transformers
Safetensors
modernbert
typed-decisions
decision-index
decision-model
cross-encoder
text-embeddings-inference
Instructions to use tasksource/tasksource-decider-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tasksource/tasksource-decider-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tasksource/tasksource-decider-nano")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("tasksource/tasksource-decider-nano") model = AutoModel.from_pretrained("tasksource/tasksource-decider-nano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
correct Tasksource rows to heterogeneous-split probes
Browse files
README.md
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| Typed Decisions | 42.6% |
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| AG News | 73.8% |
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| Emotion | 49.0% |
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| Tasksource, unseen tasks (all three judgment types) | 46.8% |
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| Tasksource, unseen test tasks (all three judgment types) | 49.7% |
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| Typed Decisions | 42.6% |
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| AG News | 73.8% |
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| Emotion | 49.0% |
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