Instructions to use Maxkillor/MythTrans_llama318B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Maxkillor/MythTrans_llama318B with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Maxkillor/MythTrans_llama318B",
	filename="MythTrans_llama318B-unsloth.F16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Maxkillor/MythTrans_llama318B with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Maxkillor/MythTrans_llama318B:F16
# Run inference directly in the terminal:
llama-cli -hf Maxkillor/MythTrans_llama318B:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Maxkillor/MythTrans_llama318B:F16
# Run inference directly in the terminal:
llama-cli -hf Maxkillor/MythTrans_llama318B:F16

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 Maxkillor/MythTrans_llama318B:F16
# Run inference directly in the terminal:
./llama-cli -hf Maxkillor/MythTrans_llama318B:F16

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 Maxkillor/MythTrans_llama318B:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Maxkillor/MythTrans_llama318B:F16

Use Docker

docker model run hf.co/Maxkillor/MythTrans_llama318B:F16

LM Studio
Jan
Ollama
How to use Maxkillor/MythTrans_llama318B with Ollama:
```
ollama run hf.co/Maxkillor/MythTrans_llama318B:F16
```

Unsloth Studio new

How to use Maxkillor/MythTrans_llama318B 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 Maxkillor/MythTrans_llama318B 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 Maxkillor/MythTrans_llama318B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Maxkillor/MythTrans_llama318B to start chatting

Docker Model Runner
How to use Maxkillor/MythTrans_llama318B with Docker Model Runner:
```
docker model run hf.co/Maxkillor/MythTrans_llama318B:F16
```

Lemonade

How to use Maxkillor/MythTrans_llama318B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Maxkillor/MythTrans_llama318B:F16

Run and chat with the model

lemonade run user.MythTrans_llama318B-F16

List all available models

lemonade list

🌟 MythTrans_llama318B 🌟

Unleashing the power of AI to breathe life into mythical creatures in Classical Chinese!

This fine-tuned model, MythTrans_llama318B, is a celebration of the **Classic of Mountains and Seas (山海經)**—an ancient masterpiece of Chinese mythology. It is specifically designed to translate English descriptions of mythical monsters into the elegance and depth of Classical Chinese. Through meticulous fine-tuning with bilingual data derived from the Classic of Mountains and Seas and its English translations (originally from modern Chinese), this model bridges the ancient and the modern, bringing mythical beasts to life like never before.

Whether you're a researcher, mythology enthusiast, or simply fascinated by the power of language, this model offers a unique way to explore and reimagine the mythical world of ancient China.

This model works well on LM Studio.

✨ Key Features

Base Model: LLaMA 3.1 8B
Purpose: Translating English descriptions of mythical monsters into Classical Chinese with literary precision and poetic beauty.
Training Data: A bilingual dataset from the Classic of Mountains and Seas (山海經) and its English translations derived from modern Chinese.
License: CC BY-NC 4.0 (Non-commercial use only, with proper attribution.)

🔍 Why Use This Model?

Explore Ancient Literature: Dive into the rich literary heritage of Classical Chinese with the help of AI.
Rediscover Mythical Creatures: Experience the mystical beasts of the Classic of Mountains and Seas in their original poetic glory.
For Everyone: Perfect for researchers, language enthusiasts, and anyone captivated by the intersection of AI and mythology.

Download this model today and let AI transport you to a world of ancient legends and mythical monsters, reimagined in the beauty of Classical Chinese!

Author: Max Lee Tik Fan

📊 Model Comparison

Example 1:

Vanilla Llama 3.1 8B Output:

The Ember Wyrm

MythTrans_llama318B Output:

The Ember Wyrm

Example 2:

Vanilla Llama 3.1 8B Output:

The Shadow Hag

MythTrans_llama318B Output:

The Shadow Hag

🌏 中文介紹

用人工智能的力量，將古代神話中的怪獸帶回文言文的詩意世界！

MythTrans_llama318B 是一款基於《山海經》精調的模型，專門用於將 英文怪獸描述翻譯成典雅的文言文。
這款模型採用了來自《山海經》全文及其由現代中文翻譯成的英文文本數據，經過精心訓練，讓每一段翻譯都能展現古文的美感與文學深度，為這部傳奇古籍注入新的生命力。

無論您是 研究者、古文愛好者，還是對怪獸傳說充滿興趣的讀者，這款模型都能為您提供探索古代神話的新方式。

本模型在LM Studio上運行流暢。

✨ 模型亮點

基礎模型: LLaMA 3.1 8B
用途: 將 英文怪獸描述翻譯為文言文，保留古文的詩意與文化魅力。
訓練數據: 精選自《山海經》全文及其由現代中文翻譯的英文版本。
授權許可: CC BY-NC 4.0 (僅限非商業用途，需標註來源。)

🔍 為什麼選擇這款模型？

探索古代文學: 以全新的方式了解 文言文的豐富遺產。
重現神話怪獸: 透過 AI，重新發現《山海經》中的 神話怪獸。
適合多種用途: 無論是 研究者、語言愛好者，還是對 AI 與神話結合感興趣的讀者，都能從中受益。

立即下載這款模型，讓人工智能帶您穿越時間，探索古老傳說中的神話世界，重現那些令人驚嘆的怪獸傳說！

作者: Max Lee Tik Fan

📊 模型比較

Example 1:

原始 Llama 3.1 8B 結果:

The Ember Wyrm

MythTrans_llama318B 微調模型結果:

The Ember Wyrm

Example 2:

原始 Llama 3.1 8B 結果:

The Shadow Hag

MythTrans_llama318B 微調模型結果:

The Shadow Hag

📜 License

This model is licensed under CC BY-NC 4.0.
It is free for non-commercial use, but proper attribution is required. For full terms, visit CC BY-NC 4.0.

🛠️ Technical Details

Pipeline: Translation
Languages Supported: English (en), Classical Chinese (zh)
Tags: unsloth, translation, mythology

Let AI help you rediscover ancient myths and bridge cultures through the art of language!

Downloads last month: 17

Safetensors

Model size

8B params

Tensor type

BF16

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