Instructions to use keisuke-miyako/springsea-0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use keisuke-miyako/springsea-0.2 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 keisuke-miyako/springsea-0.2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/springsea-0.2:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf keisuke-miyako/springsea-0.2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/springsea-0.2:Q4_K_M

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 keisuke-miyako/springsea-0.2:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf keisuke-miyako/springsea-0.2:Q4_K_M

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 keisuke-miyako/springsea-0.2:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf keisuke-miyako/springsea-0.2:Q4_K_M

Use Docker

docker model run hf.co/keisuke-miyako/springsea-0.2:Q4_K_M

LM Studio
Jan
Ollama
How to use keisuke-miyako/springsea-0.2 with Ollama:
```
ollama run hf.co/keisuke-miyako/springsea-0.2:Q4_K_M
```
Unsloth Desktop

How to use keisuke-miyako/springsea-0.2 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf keisuke-miyako/springsea-0.2:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "keisuke-miyako/springsea-0.2:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use keisuke-miyako/springsea-0.2 with Docker Model Runner:
```
docker model run hf.co/keisuke-miyako/springsea-0.2:Q4_K_M
```

Lemonade

How to use keisuke-miyako/springsea-0.2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull keisuke-miyako/springsea-0.2:Q4_K_M

Run and chat with the model

lemonade run user.springsea-0.2-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use keisuke-miyako/springsea-0.2 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf keisuke-miyako/springsea-0.2:Q4_K_M

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 keisuke-miyako/springsea-0.2:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use keisuke-miyako/springsea-0.2 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf keisuke-miyako/springsea-0.2:Q4_K_M

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 "keisuke-miyako/springsea-0.2:Q4_K_M" \
  --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"

A fine-tuned code generation model for 4D programming

Overview

SpringSea is a fine-tuned version of google/gemma-4-E2B-it, specialized for generating, completing, and reasoning about 4D code — the proprietary language powering 4D application development.

The goal of this project is to develop a coding assistant model that understands the full 4D development ecosystem.

LoRA Training Details

0423-02 💥

Classes are over-indexing.

Type	Size	Rank	Alpha	Warmup	Rate	Epochs	Rows	Steps	Duration
Text	4.19 MB	32	64	0.1	2e-4	3	1298	489	55:42

0423-01 💥

Language is not activated.

Type	Size	Rank	Alpha	Warmup	Rate	Epochs	Rows	Steps	Duration
Text	4.19 MB	32	64	0.1	2e-5	1	163	1298	17:41

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Safetensors

Model size

5B params

Tensor type

BF16

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Model tree for keisuke-miyako/springsea-0.2

Base model

google/gemma-4-E2B

Finetuned

google/gemma-4-E2B-it

Quantized

(363)

this model

keisuke-miyako
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springsea-0.2

Overview

LoRA Training Details

Model tree for keisuke-miyako/springsea-0.2

Datasets used to train keisuke-miyako/springsea-0.2