Instructions to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF", filename="hy-mt1.5-1.8b-q5_k_m.gguf", )
llm.create_chat_completion( messages = "\"Меня зовут Вольфганг и я живу в Берлине\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF 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 Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_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 Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_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 Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
Use Docker
docker model run hf.co/Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF with Ollama:
ollama run hf.co/Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
- Unsloth Studio
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-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 Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-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 Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF with Docker Model Runner:
docker model run hf.co/Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
- Lemonade
How to use Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF:Q5_K_M
Run and chat with the model
lemonade run user.Hy-MT1.5-1.8B-Q5_K_M-GGUF-Q5_K_M
List all available models
lemonade list
Hy-MT1.5-1.8B Q5_K_M GGUF
tencent/HY-MT1.5-1.8B を Q5_K_M (5.78 BPW) で量子化した GGUF ファイルです。
- 元モデル: tencent/HY-MT1.5-1.8B (HunYuanDenseV1ForCausalLM, 1.8B params)
- 量子化: Q5_K_M (
llama-quantizefrom llama.cpp b9093) - ファイルサイズ: 1.20 GiB (3.3 GiB FP16 → Q5_K_M)
- 対応言語: 33 言語 (1056 翻訳方向)
- 用途: iOS アプリ DokodemoTranslate のローカル翻訳エンジン
変更点 (Tencent HY License Section 3.b に基づく明示)
Q5_K_M quantization by DokodemoTranslate maintainer, derived from
tencent/HY-MT1.5-1.8B(FP16 safetensors). Conversion pipeline:convert_hf_to_gguf.py --outtype f16→llama-quantize ... Q5_K_M. No model architecture, weights training, or vocabulary modification.
ライセンス
本モデルは Tencent HY Community License Agreement に基づき配布されています。
Tencent HY is licensed under the Tencent HY Community License Agreement, Copyright © 2025 Tencent. All Rights Reserved. The trademark rights of "Tencent HY" are owned by Tencent or its affiliate.
Powered by Tencent HY.
重要: 地域制限 (Territory Restriction)
本ライセンスは EU・英国・韓国を Territory から除外しています (License Section 1.l, 5.c)。
"Territory" shall mean the worldwide territory, excluding the territory of the European Union, United Kingdom and South Korea.
You must not use, reproduce, modify, distribute, or display the Tencent HY Works ... outside the Territory.
EU・UK・KR でのご利用は許諾範囲外です。フルライセンスは LICENSE を参照。
推奨推論パラメータ
{
"top_k": 20,
"top_p": 0.6,
"repetition_penalty": 1.05,
"temperature": 0.7
}
system prompt はデフォルトで設定しません (元モデル仕様)。
プロンプト
中国語が source または target の場合 (ZH<=>XX):
将以下文本翻译为{target},注意只需要输出翻译后的结果,不要额外解释:
{source_text}
それ以外 (XX<=>XX):
Translate the following segment into {target}, without additional explanation.
{source_text}
llama.cpp での利用
llama.cpp b9093 以降で hunyuan-dense アーキテクチャがサポートされます。
./llama-cli -m hy-mt1.5-1.8b-q5_k_m.gguf \
-p "<|hy_begin▁of▁sentence|><|hy_User|>Translate the following segment into Japanese, without additional explanation.\n\nHello, world.<|hy_Assistant|>" \
--temp 0.7 --top-k 20 --top-p 0.6 --repeat-penalty 1.05 \
--no-context-shift -n 256
⚠️ EOS トークンの注意
convert_hf_to_gguf.py が tokenizer.ggml.eos_token_id を 誤って 3 ('$') として書き込みます (本来は 120020 = <|hy_place▁holder▁no▁2|>)。'$' を含むテキストで生成が即停止する潜在バグになります。
回避策: 自前で stop tokens を構築する。例 (Swift):
// llama_vocab_is_eog は信用せず、専用トークンを tokenize して逆引き
let stopTokens: Set<llama_token> = [
tokenize("<|hy_place▁holder▁no▁2|>", special: true),
tokenize("<|hy_User|>", special: true),
]
クレジット
- 元モデル: Tencent Hunyuan
- 技術レポート: HY-MT1.5 Technical Report
- 量子化ツール: llama.cpp
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Model tree for Toshizo513/Hy-MT1.5-1.8B-Q5_K_M-GGUF
Base model
tencent/HY-MT1.5-1.8B