TimeCapsule Gemma 3n 2.7B Slice (FP16 GGUF)
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 usingllama.cpp
’sconvert_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
- Downloads last month
- 6
Hardware compatibility
Log In
to view the estimation
16-bit
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support