---

license: apache-2.0

language:

- en

tags:

- meetara

- meeTARA

- gguf

- instruction-tuned

base_model: unknown

pipeline_tag: text-generation

---

meetara-gemma4-e2b-it (meeTARA Gemma 4 distribution)

This is a meeTARA-branded export of the official open-weights checkpoint unknown

(Gemma 4, instruction-tuned). Gemma-native turn formatting is preserved, and meeTARA default

system behavior is injected only when the caller does not provide a system message, so

multimodal formatting, tool calling, and thinking modes stay compatible with Transformers and

current llama.cpp converters.

me²TARA = Mental & Emotional Empathetic Technology for Adaptive Response & Assistance.

meeTARA welcome and response structure (optional)

This folder includes meetara_default_system_en.txt: the same welcome + structured-response

intent as the v3 "simple" ChatML block, in plain text for you to pass as a system (or

developer) message in your app or API. The same default content is also mirrored into Gemma-native

template metadata so behavior remains present when no explicit system message is provided.

Why not the v3 "enhanced" ChatML template?

convert_to_gguf_meetara_v3_enhanced.py injects a large Qwen-style ChatML chat template. Gemma 4

expects Google's <|turn|> template and special tokens; mixing formats would produce broken

prompts. For Gemma, use this script for GGUF packaging; use meetara_default_system_en.txt plus

your app, or a Gemma-native fine-tune, if you need meeTARA behavior inside the stack.

GGUF build

Built with repo llama.cpp:

python llama.cpp/convert_hf_to_gguf.py <this_folder> --outfile meetara-gemma4-e2b-it-Q4_K_M.gguf
# optional vision/audio projector:
python llama.cpp/convert_hf_to_gguf.py <this_folder> --mmproj --outfile meetara-vl-gemma4-e2b-it.gguf

License

Apache 2.0 (same as upstream Gemma 4).

Credits

Weights and tokenizer: Google DeepMind (unknown). Packaging: meeTARA project.