The Code Reasoning Epert (for) Project Exploration
The Model
Attribute
Size
Modalities
Domain
CRePE Mini
3B
Text + Image + Video in, Text out
FIM / Autocomplete
Capabilities
CRePE Mini was trained on a massive corpus of code samples, from The Trellis to other open datasets.
This model is built for code assistance, not agentic coding. Capable of FIM tasks, light code review, and making smaller utility files
How to Run
I recommend using LM Studio for running GRaPE / CRePE Models, and have generally found these sampling parameters to work best:
Name
Value
Temperature
0.6
Top K Sampling
40
Repeat Penalty
1
Top P Sampling
0.85
Min P Sampling
0.05
CRePE Mini as a Model
CRePE Mini is more an experiment than anything. This model was trained on The Trellis dataset for code samples, and all code examples from the GRaPE Instruct dataset. And thus has become an apt coder for light tasks. It is in no way designed to replace coders, only to empower them.
Architecture
CRePE Mini: Built on the GRaPE Mini's architecture
Notes
The GRaPE Family started all the way back in August of 2025, meaning these models are severely out of date on architecture, and training data.
GRaPE 2 will come sooner than the GRaPE 1 family had, and will show multiple improvements.
There are no benchmarks for GRaPE 1 Models due to the costly nature of running them, as well as prioritization of newer models.
Updates for GRaPE 2 models will be posted here on Huggingface, as well as Skinnertopia
