Zero-Shot Classification
Transformers
Safetensors
matilda_jev
feature-extraction
matilda
jev
decision-model
classification
maincode
custom_code
Instructions to use Maincode/Matilda-Jev-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maincode/Matilda-Jev-v1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Maincode/Matilda-Jev-v1.5", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Maincode/Matilda-Jev-v1.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# MATILDA JEV v1.5 by Maincode
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material, and this release was chosen after comparing experimental scores.
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The numbers are not an independent held-out generalization estimate. The full
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suite evaluated text decisions; vision inference was not validated for this
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pipeline_tag: zero-shot-classification
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---
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# MATILDA JEV v1.5 by Maincode
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material, and this release was chosen after comparing experimental scores.
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The numbers are not an independent held-out generalization estimate. The full
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suite evaluated text decisions; vision inference was not validated for this
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release.
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