bRadu/translategemma-4b-it-novision

Text-only (no-vision) conversion of google/translategemma-4b-it, saved in FP16 (safetensors). The tokenizer is set from google/gemma-3-1b-it.

What this is

This repo contains a converted Gemma3ForCausalLM checkpoint extracted from the language component of the original multimodal model:

• Source: google/translategemma-4b-it
• Target architecture: Gemma3ForCausalLM (text-only)
• Precision: float16 weights
• Removed components: vision tower / multimodal-only parts

Intended use

• Translation and text generation with the same chat-format style expected by TranslateGemma.
• Efficient local or server inference where vision capability is not needed.

Recommended system prompt (see https://arxiv.org/pdf/2601.09012 for src codes)

SYSTEM_PROMPT = """You are a professional {source_lang} ({src_lang_code}) to {target_lang}
({tgt_lang_code}) translator. Your goal is to accurately convey the meaning and
nuances of the original {source_lang} text while adhering to {target_lang} grammar,
vocabulary, and cultural sensitivities. Produce only the {target_lang}
translation, without any additional explanations or commentary. Please translate
the following {source_lang} text into {target_lang}:\n"""

How to use (different chat template from the original google/translategemma-4b-it page, similar to google/gemma-3-1b-it)

messages = [
  {
    "role" : "system",
    "content": SYSTEM_PROMPT
  },
  {
    "role": "user",
    "content": <TEXT_TO_BE_TRANSLATED>
  }
]

from unsloth import FastModel

model, tokenizer = FastModel.from_pretrained(model)

tokenizer.apply_chat_template(messages)