Quantization
- Scheme:
FP8_DYNAMIC (FP8 E4M3 weights, per-token dynamic FP8 activations), produced with llm-compressor (quantization_scheme recorded in recipe.yaml).
- All
Linear layers of the language model are quantized; the vision tower, multi-modal projector, lm_head, and embeddings are kept in BF16. MTP (multi-token prediction) weights are preserved.
- Format: compressed-tensors safetensors — load directly with vLLM (
quantization="compressed-tensors") or transformers.
Consistency validation
Measured on an NVIDIA A100 against the original BF16 checkpoint (greedy decoding, official translation prompt):
Table with columns: Metric, BF16, FP8, Delta| Metric | BF16 | FP8 | Delta |
|---|
| Perplexity (fixed corpus) | 2.7722 | 2.7838 | +0.42% |
| zh→en generation identical | — | — | yes |
| en→zh generation identical | — | — | yes |
Usage
vllm serve IndexTeam/Index-Translate-9B-FP8 --host 127.0.0.1 --port 8000 --max-model-len 4096
Translation prompt format (greedy decoding, temperature=0 recommended; chat template with enable_thinking: false):
请将以下文本翻译为{target-language},直接输出翻译结果,不要进行任何解释。 {source-text}
Prompting & constrained translation (instTrans)
Beyond plain translation, the models follow the instTrans constrained-translation format. The official client wraps requests into the canonical structure 【源文】<text> + numbered 1. 【硬性要求】<hard constraints> + 2. 【注意】<soft constraints> + suffix instructions:
- Hard constraints (binary, must hold): strict terminology glossary enforcement (e.g.
碳纤维:carbon fiber, 抗裂缝:crack resistance), and format/structure preservation for JSON/CSV/code/placeholders.
- Soft constraints (graded): tone & style adaptation (e.g. formal business-email register), domain/word-sense disambiguation (e.g. plant → 工厂 in an industrial context), cross-sentence consistency, LaTeX preservation.
- Syllable-controlled translation (dubbing): use the Index-Homura checkpoints (IndexTeam/Index-Homura-2B/9B), which strictly respect a target syllable budget and can be combined with glossaries.
Full prompt reference: github.com/bilibili/Index-Translate (Instruction Following section, docs/prompts.md, inference/llm/cases/).
See the base model card for the full instTrans constrained-translation format and serving presets. GGUF builds for local inference are published in Index-Translate-9B-GGUF.
Quantized and published by the Index team, 2026-10-03.