Instructions to use szdr/jaqmd-qe-gemma-4-e2b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use szdr/jaqmd-qe-gemma-4-e2b-it with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-4-e2b-it-unsloth-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "szdr/jaqmd-qe-gemma-4-e2b-it")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use szdr/jaqmd-qe-gemma-4-e2b-it 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 szdr/jaqmd-qe-gemma-4-e2b-it:BF16
# Run inference directly in the terminal:
llama cli -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16
# Run inference directly in the terminal:
llama cli -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

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 szdr/jaqmd-qe-gemma-4-e2b-it:BF16
# Run inference directly in the terminal:
./llama-cli -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

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 szdr/jaqmd-qe-gemma-4-e2b-it:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Use Docker

docker model run hf.co/szdr/jaqmd-qe-gemma-4-e2b-it:BF16

LM Studio
Jan
Ollama
How to use szdr/jaqmd-qe-gemma-4-e2b-it with Ollama:
```
ollama run hf.co/szdr/jaqmd-qe-gemma-4-e2b-it:BF16
```

Unsloth Studio

How to use szdr/jaqmd-qe-gemma-4-e2b-it with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for szdr/jaqmd-qe-gemma-4-e2b-it to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for szdr/jaqmd-qe-gemma-4-e2b-it to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for szdr/jaqmd-qe-gemma-4-e2b-it to start chatting

How to use szdr/jaqmd-qe-gemma-4-e2b-it with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "szdr/jaqmd-qe-gemma-4-e2b-it:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use szdr/jaqmd-qe-gemma-4-e2b-it with Docker Model Runner:
```
docker model run hf.co/szdr/jaqmd-qe-gemma-4-e2b-it:BF16
```

Lemonade

How to use szdr/jaqmd-qe-gemma-4-e2b-it with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Run and chat with the model

lemonade run user.jaqmd-qe-gemma-4-e2b-it-BF16

List all available models

lemonade list

Hermes Agent

How to use szdr/jaqmd-qe-gemma-4-e2b-it with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use szdr/jaqmd-qe-gemma-4-e2b-it with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf szdr/jaqmd-qe-gemma-4-e2b-it:BF16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "szdr/jaqmd-qe-gemma-4-e2b-it:BF16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

jaqmd-qe-gemma-4-e2b-it

unsloth/gemma-4-E2B-it を LoRA で fine-tune した、日本語検索エンジン向け Query Expansion モデル。

入力クエリ (query) に対し、以下 3 種を含む JSON を出力する:

lex: 語彙検索(BM25等)向けの語句・表記ゆれ配列
vec: 意味検索(embedding)向けの言い換え1文
hyde: HyDE 用の仮想文書

入出力フォーマット

入力はチャットテンプレートの user ターンにクエリをそのまま渡す (system prompt は使用していない)。出力はキー順 lex -> vec -> hyde 固定の compact JSON 文字列。

user:  木魚
model: {"lex":[...],"vec":"...","hyde":"..."}

注意 (thinking の無効化)

ベースモデルはデフォルトで thinking が有効だが、本モデルは thinking なし (JSON 直答) で学習している。推論時は明示的に無効化すること。

transformers: apply_chat_template(..., enable_thinking=False)
llama.cpp: --reasoning false を使うこと。 --chat-template-kwargs '{"enable_thinking":false}' は Gemma 4 の同梱チャットテンプレートの既知の不具合(enable_thinking の分岐が逆転している)により効かない/不安定なビルドがある。 --reasoning false はテンプレートのレンダリングに依存せず推論パラメータ側で reasoning を止めるため、こちらを使う。

GGUF

gguf/ 以下に llama.cpp / Ollama 用の量子化済み GGUF を同梱。

Downloads last month: 31

GGUF

Model size

5B params

Architecture

gemma4

Hardware compatibility

4-bit

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Model tree for szdr/jaqmd-qe-gemma-4-e2b-it

Base model

google/gemma-4-E2B

Finetuned

google/gemma-4-E2B-it

Finetuned

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