---
license: gemma
language:
- en
- zh
base_model: twinkle-ai/gemma-3-4B-T1-it
library_name: transformers
tags:
- Taiwan
- R.O.C
- zhtw
- SLM
- Gemma-3
- gemma3
- llama-cpp
- gguf-my-repo
datasets:
- lianghsun/tw-reasoning-instruct
- lianghsun/tw-contract-review-chat
- minyichen/tw-instruct-R1-200k
- minyichen/tw_mm_R1
- minyichen/LongPaper_multitask_zh_tw_R1
- nvidia/Nemotron-Instruction-Following-Chat-v1
metrics:
- accuracy
model-index:
- name: gemma-3-4B-T1-it
  results:
  - task:
      type: question-answering
      name: Single Choice Question
    dataset:
      name: tmmlu+
      type: ikala/tmmluplus
      config: all
      split: test
      revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
    metrics:
    - type: accuracy
      value: 47.44
      name: single choice
  - task:
      type: question-answering
      name: Single Choice Question
    dataset:
      name: mmlu
      type: cais/mmlu
      config: all
      split: test
      revision: c30699e
    metrics:
    - type: accuracy
      value: 59.13
      name: single choice
  - task:
      type: question-answering
      name: Single Choice Question
    dataset:
      name: tw-legal-benchmark-v1
      type: lianghsun/tw-legal-benchmark-v1
      config: all
      split: test
      revision: 66c3a5f
    metrics:
    - type: accuracy
      value: 44.18
      name: single choice
---

# tedslin/gemma-3-4B-T1-it-Q4_K_M-GGUF
This model was converted to GGUF format from [`twinkle-ai/gemma-3-4B-T1-it`](https://huggingface.co/twinkle-ai/gemma-3-4B-T1-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/twinkle-ai/gemma-3-4B-T1-it) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo tedslin/gemma-3-4B-T1-it-Q4_K_M-GGUF --hf-file gemma-3-4b-t1-it-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo tedslin/gemma-3-4B-T1-it-Q4_K_M-GGUF --hf-file gemma-3-4b-t1-it-q4_k_m.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo tedslin/gemma-3-4B-T1-it-Q4_K_M-GGUF --hf-file gemma-3-4b-t1-it-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo tedslin/gemma-3-4B-T1-it-Q4_K_M-GGUF --hf-file gemma-3-4b-t1-it-q4_k_m.gguf -c 2048
```