Instructions to use kuzaai/kuza-gemma-4-e2b-old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kuzaai/kuza-gemma-4-e2b-old with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kuzaai/kuza-gemma-4-e2b-old with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
Use Docker
docker model run hf.co/kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use kuzaai/kuza-gemma-4-e2b-old with Ollama:
ollama run hf.co/kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
- Unsloth Desktop
- Docker Model Runner
How to use kuzaai/kuza-gemma-4-e2b-old with Docker Model Runner:
docker model run hf.co/kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
- Lemonade
How to use kuzaai/kuza-gemma-4-e2b-old with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kuzaai/kuza-gemma-4-e2b-old:UD-Q4_K_XL
Run and chat with the model
lemonade run user.kuza-gemma-4-e2b-old-UD-Q4_K_XL
List all available models
lemonade list
- Atomic Chat
Kuza Gemma 4 E2B
Full training-run archive for Kuza (East Africa agricultural assistant),
fine-tuned from unsloth/gemma-4-E2B-it-qat-q4_0-unquantized.
Weights, logs, checkpoints, GGUFs, and provenance are stored with the same
layout as $KUZA_WORK_DIR/kuza-gemma-4-e2b/.
This derivative is subject to the Gemma license.
Training mix
- 100% English train from
kuzaai/kuza_sft_english - 35% Swahili from
kuzaai/kuza_sft_swahili - 8%
HuggingFaceH4/no_robots - 5% adversarial from
kuzaai/kuza_sft_adversarial - all multiturn from
kuzaai/kuza_sft_multiturn
LoRA: RsLoRA r=32, alpha=64, QAT int4.
Sequence length 1024, 2 epochs, LR 2e-05.
Thinking is off. GGUFs are text-only (PLE kept; vision/audio dropped).
Files
adapter/โ PEFT adapter, tokenizer, SFT metrics and manifeststraining/โ Trainer checkpoints includingcheckpoint-bestmerged_bf16/โ text-only merged Hugging Face BF16 weightsreference/โ text-only BF16 GGUF (kuza-bf16.gguf) and smoke logimatrix/โ calibration corpus, eval corpus, imatrix, logsquants/โ quantized GGUF candidates:q4_k_m_ud_style/kuza-q4_k_m-ud-style.gguf(q4_k_m)ud_q4_k_xl/kuza-ud-q4_k_xl.gguf(q4_k_m)q4_0_qat_aligned/kuza-q4_0-qat-aligned.gguf(q4_0)screen/โ GPU KLD diagnostic, hidden-set scores, andresults.jsonwinnerprovenance/โ copied adapter metrics, recipes, screen JSONupload_manifest.jsonโ path, size, and sha256 for every uploaded file
Download
huggingface-cli download kuzaai/kuza-gemma-4-e2b --local-dir ./kuza-gemma-4-e2b
screen/results.json ranks by hidden-set accuracy, then GGUF size, then GPU
TPS. Do not treat GPU TPS as an ADTC laptop measurement.
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Model tree for kuzaai/kuza-gemma-4-e2b-old
Base model
google/gemma-4-E2B