Instructions to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF",
	filename="swallow-3-8b-sqlcoder-2x8b.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF: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 keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF: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 keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with Ollama:
```
ollama run hf.co/keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF 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 keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF 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 keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF to start chatting

Docker Model Runner
How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with Docker Model Runner:
```
docker model run hf.co/keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M
```

Lemonade

How to use keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull keitokei1994/swallow-3-8B-sqlcoder-2x8B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.swallow-3-8B-sqlcoder-2x8B-GGUF-Q4_K_M

List all available models

lemonade list

モデルの説明(English explanation is below.)

このモデルは、MergeKitツールを使用して作成されたMixture of Experts (MoE) 言語モデルをGGUF形式で量子化したものです。

量子化していないものはこちら

デモはこちら

モデルの詳細

モデル名: swallow-3-8B-sqlcoder-2x8B-GGUF
モデルアーキテクチャ: Mixture of Experts (MoE)
ベースモデル:
- aixsatoshi/Llama3-Swallow-8B-instruct-vector-merged
- defog/llama-3-sqlcoder-8b
マージツール: MergeKit

このMoEモデルは、Llama3-Swallow-8B-instruct-vector-mergedの日本語能力とLlama-3-sqlcoder-8bのSQL生成能力を組み合わせることで、より強力で多機能な言語モデルを目指しています。

特徴

日本語と英語の両方に対応
Llama3-Swallow-8B-instruct-vector-mergedによる優れた日本語処理能力
Llama-3-sqlcoder-8bによる高度なSQL生成と処理能力

要求スペック

Q4_K_M量子化モデルであれば、RTX3060 12GBでフルロード可能です。筆者はWSL2やGoogle Colaboratotry Proでの作成後、Llama.cppとLMstudioにて動作確認を行っています。

Model Description

This model is a Mixture of Experts (MoE) language model created using the MergeKit tool. The gguf version can be found こちら.

Model Details

Model Name: swallow-3-8B-sqlcoder-2x8B-GGUF
Model Architecture: Mixture of Experts (MoE)
Base Models:
- aixsatoshi/Llama3-Swallow-8B-instruct-vector-merged
- defog/llama-3-sqlcoder-8b
Merge Tool: MergeKit

This MoE model aims to create a more powerful and versatile language model by combining the Japanese language capabilities of Llama3-Swallow-8B-instruct-vector-merged with the SQL generation abilities of Llama-3-sqlcoder-8b.

Features

Support for both Japanese and English languages
Excellent Japanese processing capabilities from Llama3-Swallow-8B-instruct-vector-merged
Advanced SQL generation and processing capabilities from Llama-3-sqlcoder-8b

System Requirements

If using the Q4_K_M quantized model, it can be fully loaded on an RTX3060 12GB. The author has created the model using WSL2 and Google Colaboratory Pro, and has tested it using Llama.cpp and LMstudio.

Downloads last month: 57

GGUF

Model size

14B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

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swallow-3-8B-sqlcoder-2x8B-GGUF