Instructions to use ILKT/2024-06-17_21-37-12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ILKT/2024-06-17_21-37-12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ILKT/2024-06-17_21-37-12", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ILKT/2024-06-17_21-37-12", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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Spaces using ILKT/2024-06-17_21-37-12 11
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mteb/leaderboard_legacy
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SmileXing/leaderboard
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sq66/leaderboard_legacy
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reader-1/1
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shiwan7788/leaderboard-uni
Evaluation results
- accuracy on MTEB MassiveIntentClassificationtest set self-reported0.137
- accuracy on MTEB MassiveIntentClassificationvalidation set self-reported0.125
- accuracy on MTEB MassiveScenarioClassificationtest set self-reported0.210
- accuracy on MTEB MassiveScenarioClassificationvalidation set self-reported0.204
- accuracy on MTEB CBDtest set self-reported0.542
- accuracy on MTEB PolEmo2.0-INtest set self-reported0.338
- accuracy on MTEB PolEmo2.0-OUTtest set self-reported0.278
- accuracy on MTEB AllegroReviewstest set self-reported0.207