Instructions to use IndexTeam/Index-Translate-9B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IndexTeam/Index-Translate-9B-FP8 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="IndexTeam/Index-Translate-9B-FP8")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("IndexTeam/Index-Translate-9B-FP8") model = AutoModelForMultimodalLM.from_pretrained("IndexTeam/Index-Translate-9B-FP8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add README.md
Browse files
README.md
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---
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base_model: IndexTeam/Index-Translate-9B
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library_name: transformers
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tags:
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- fp8
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- compressed-tensors
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- translation
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- index
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license: apache-2.0
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---
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# Index-Translate-9B-FP8
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Official FP8 (W8A8) quantization of [IndexTeam/Index-Translate-9B](https://huggingface.co/IndexTeam/Index-Translate-9B), part of the **Index-Translate** multilingual translation model family (150 languages, terminology/format-constrained translation, controlled dubbing translation, long-document translation).
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- Technical report: [Index-Translate: A Multilingual Translation Model Family](https://arxiv.org/abs/2609.40181)
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- Code: [github.com/bilibili/Index-Translate](https://github.com/bilibili/Index-Translate)
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## Quantization
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- Scheme: `FP8_DYNAMIC` (FP8 E4M3 weights, per-token dynamic FP8 activations), produced with [llm-compressor](https://github.com/vllm-project/llm-compressor) (`quantization_scheme` recorded in `recipe.yaml`).
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- 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.
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- Format: [compressed-tensors](https://github.com/neuralmagic/compressed-tensors) safetensors — load directly with vLLM (`quantization="compressed-tensors"`) or transformers.
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## Consistency validation
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Measured on an NVIDIA A100 against the original BF16 checkpoint (greedy decoding, official translation prompt):
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| Metric | BF16 | FP8 | Delta |
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|:-------|-----:|----:|------:|
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| Perplexity (fixed corpus) | 2.7722 | 2.7838 | +0.42% |
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| zh→en generation identical | — | — | yes |
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| en→zh generation identical | — | — | yes |
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## Usage
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```bash
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vllm serve IndexTeam/Index-Translate-9B-FP8 --host 127.0.0.1 --port 8000 --max-model-len 4096
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```
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Translation prompt format (greedy decoding, temperature=0 recommended):
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```text
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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。
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{source-text}
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```
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See the [base model card](https://huggingface.co/IndexTeam/Index-Translate-9B) for the full instTrans constrained-translation format and serving presets. GGUF builds for local inference are published in [Index-Translate-9B-GGUF](https://huggingface.co/IndexTeam/Index-Translate-9B-GGUF).
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*Quantized and published by the Index team, 2026-10-03.*
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