Text Classification
Transformers
Safetensors
decision-model
decision-making
system-one
calibrated-probabilities
distillation
embeddinggemma
solar-decide-flash
Instructions to use SargeDev/Solar-JEV-Gemma-embed-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SargeDev/Solar-JEV-Gemma-embed-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SargeDev/Solar-JEV-Gemma-embed-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SargeDev/Solar-JEV-Gemma-embed-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
28 days ago
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State training dataset in card body
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29 days ago
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Add model card: method, full-split results, limitations, attribution
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Add model card: method, full-split results, limitations, attribution
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Add model card: method, full-split results, limitations, attribution
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Solar-JEV-Gemma-embed-2: frozen EmbeddingGemma-2 body + linear heads distilling Solar Decide Flash calibrated judgments (corpus v4, 756k rows)
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initial commit
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