The TempestLLM model collection consists of the base foundation model, an instruction fine-tuned (SFT) version, and other related variants.
AI & ML interests
Our goal is to train the largest possible SSM model while minimizing infrastructure requirements. This approach reduces both economic and environmental impact without significantly compromising the model's linguistic performance.
A suite of models and a dataset designed to assess the quality of natural language and code data.
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Cyrile/EuroBERT-210m-Quality
Text Classification • 0.2B • Updated • 28 • 1 -
Cyrile/EuroBERT-210m-Quality-NL
Text Classification • 0.2B • Updated • 25 • 1 -
Cyrile/EuroBERT-210m-Quality-CL
Text Classification • 0.2B • Updated • 21 • 1 -
Cyrile/dataset-quality
Viewer • Updated • 44.8k • 74 • 1
The TempestLLM model collection consists of the base foundation model, an instruction fine-tuned (SFT) version, and other related variants.
A suite of models and a dataset designed to assess the quality of natural language and code data.
-
Cyrile/EuroBERT-210m-Quality
Text Classification • 0.2B • Updated • 28 • 1 -
Cyrile/EuroBERT-210m-Quality-NL
Text Classification • 0.2B • Updated • 25 • 1 -
Cyrile/EuroBERT-210m-Quality-CL
Text Classification • 0.2B • Updated • 21 • 1 -
Cyrile/dataset-quality
Viewer • Updated • 44.8k • 74 • 1