This model is a 2.7 B parameter sub‑model of Gemma 3n, created using the MatFormer (Matryoshka Transformer) architecture and the Mix‑n‑Match slicing approach. It was sliced from the E4B checkpoint using the official E2.69B (layer‑level) configuration.
🧠 Intended Use
Primary use: High‑precision inference with Ollama via FP16 GGUF.
Best suited for: TimeCapsule‑SLM deep‑research workflows where latency, accuracy, and compute tradeoffs matter.
⚠️ Limitations & Considerations
Derived from a larger model — may not match the full E4B model in some evaluations.
Operates in FP16 precision — requires hardware (like A100/GPU or Ollama host) with FP16 support.
No additional quantization applied, preserving accuracy at some memory cost.
🛠 Creation Details
Parent model: google/gemma-3n-E4B-it
Slice configuration: Config for E2.69B (layer-level) from the official slicing-configs dataset
Converted from .safetensors to FP16 GGUF using llama.cpp’s convert_hf_to_gguf.py
Uploaded to this repository as: tc_mixmatch_f16.gguf
🧪 Usage Example
ollama run hf.co/bubblspace/Timecapsule2.7B-g3n-mix-match-gguf
