🧩 Model Card: hy-mt2-flash:1.8b

• Type: Text-to-Text (Translation)
• Think: No
• Tool Calling Support: No
• Base Model: tencent/Hy-MT2-1.8B
• Quantization: Q4_0
• Max Context Length: 1k tokens
• Default Context Length: 1k tokens (fixed, see note below)

▶️ Run with FastFlowLM in PowerShell:

flm run hy-mt2-flash:1.8b

⚠️ Note: Starting from FLM v1.0.6, Hy-MT2 is served as a single-turn model: every request starts from a clean KV state, and the context length is fixed at 1k tokens — context-length overrides are ignored. This matches how the model is meant to be used, one short translation request at a time.

Earlier versions allowed longer contexts. The benchmark results were measured on v1.0.5 and therefore sweep up to 16k.

📖 Prompt Guide

Prompt Format

Hy-MT2 is a dedicated translation model, not a general-purpose chat model — it has no default system prompt. There are two ways to prompt it:

Option 1: instruction + text in a single user message

将以下文本翻译为{TARGET_LANG}，注意只需要输出翻译后的结果，不要额外解释：

{TEXT}

or, in English:

Translate the following segment into {TARGET_LANG}, without additional explanation.

{TEXT}

Option 2: instruction as the system prompt, text as the user message

Pin the translation instruction as the system prompt so it isn’t re-prefilled every turn, then send only the source text as the user message:

{"role": "system", "content": "将以下文本翻译为英语，注意只需要输出翻译后的结果，不要额外解释。输出必须全部使用英语，不要输出源语言或原文"},
{"role": "user", "content": "{TEXT}"}

This is the recommended format in server mode for multi-turn or repeated translation calls (e.g. batch translating subtitle lines), since the instruction’s prefill cost is paid once instead of once per request.