feat(models): add google/translategemma-4b-it - #295
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Text-to-text translation model (Gemma 3 4B fine-tune covering 55 languages) served through the SGLang generation adapter in bfloat16 at the pinned checkpoint revision. - 4096-token prompt-plus-completion envelope with a 512-token output cap: the model card documents a 2K-token input design for translation - <end_of_turn> is the generation stop, matching the checkpoint's generation_config eos ids - trust_remote_code pinned to false; the repository ships no custom code - grammar, tool calling and image input are not advertised: the checkpoint is documented for translation only, and its chat template requires per-message source and target language codes that the chat-completions route does not carry, so callers use the generate route with the rendered translation prompt Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Included review availability: 7 reviews are currently available. Your included PR review attempts over the past 7 days set your current allowance at 8 reviews per hour. 📝 WalkthroughWalkthroughThe change adds a configuration for ChangesTranslateGemma model support
Suggested reviewers: Priority: ⬇️ Low Merge Risk: ⚪ Minimal · up to The descriptor’s limits and runtime settings are consistent with the documented model contract, so no merge-blocking risk is established. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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In `@packages/sie_server/models/google__translategemma-4b-it.yaml`:
- Line 14: Update the context_length configuration for the TranslateGemma model
to enforce the documented 2K-token prompt limit, using a combined limit of 2560
with the existing 512-token output allowance or an explicit 2048-token prompt
limit.
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packages/sie_server/models/google__translategemma-4b-it.yaml
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…context A 2560-token envelope with the 512-token output cap admits at most a 2048-token prompt, which is the input design the model card documents. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
On the engine's default attention backend the served model answered several Traditional-Chinese prompts in Simplified Chinese and its Chinese and Japanese chrF++ fell far below a transformers reference on the same prompts; with the triton backend the outputs track the reference within engine noise. Every Gemma-family descriptor in the catalog already pins triton. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Adds the model descriptor for
google/translategemma-4b-it, Google's Gemma 3 4B fine-tune for text translation across 55 languages, served through the existing SGLang generation adapter. No adapter or bundle changes.Descriptor
bfloat16on thesglangbundle at the pinned checkpoint revision;trust_remote_code: false(the repository ships no custom code).<end_of_turn>is the generation stop, matching the checkpoint'sgeneration_configeos ids (<eos>,<end_of_turn>).The README's "Translate" row is unchanged for now; it can list this model once its translation quality has been measured.
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packages/sie_server/tests/test_all_models.py,test_model_yaml_filenames.py,test_documented_model_ids.pypass with the new descriptor.🤖 Generated with Claude Code
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