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# Fi-9B
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Fi-9B is an improved [Yi-9B-200K](https://huggingface.co/01-ai/Yi-9B-200K) with extensive instruction tuning on [Fusang-V1](https://huggingface.co/datasets/wenbopan/Fusang-v1).
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Compare to Yi-9B-200K, Fi-9B gains greater capability at various downstream tasks and long-context modeling thanks to large-scale synthestic data in Fusang-V1.
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## Performance
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Fi is competitive amongst all models at ~9B size range:
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| ---------- | -------------- | ------------- | -------------- | ----------- |
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| Yi-9B-200K | 0.7167 | 0.5672 | 0.3380 | 0.6925 |
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| Fi-9B-200K | 0.7111 | **0.5728** | **0.4086** | **0.7258** |
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| Yi-9B-200K | 30.288 | 36.7071 | 72.2 |
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| Fi-9B-200K | **41.092** | **40.9536** | 46.0 |
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|-----------------|--------------------------|------------------------|----------------------|---------------------|----------------------|--------------------------|------------------------|----------------------|---------------------|----------------------|
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| Yi-9B-200K | 60.6 | 22.8 | 30.9 | 38.9 | 25.8 | 46.5 | 28.0 | 49.6 | 17.7 | 9.7 |
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| Fi-9B-200K | **63.8** | **40.2** | **36.2** | 38.0 | **26.3** | 30.0 | **75.1** | **55.6** | **30.7** | **14.1** |
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<!--### Performance on Preference TODO-->
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### Bilingual Ability
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## How to use Fi
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## Current Limitations
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This version of Fi-9B may not be able to stop generation in some scenarios. I will fix that soon.
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Compare to the original Yi-9B-200K, Fi-9B has degraded ability for code completion. This may due to lack of raw code data during instruction tuning.
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# Fi-9B
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Fi-9B is an improved [Yi-9B-200K](https://huggingface.co/01-ai/Yi-9B-200K) with extensive instruction tuning on [Fusang-V1](https://huggingface.co/datasets/wenbopan/Fusang-v1). Compared to Yi-9B-200K, Fi-9B has gained greater capability in various downstream tasks and long-context modeling thanks to the large-scale synthetic data in Fusang-V1.
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## Performance
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Fi-9B enhances its ability compared to Yi-9B-200K in most dimensions, especially in long-range modeling and bilingual (English, Chinese) understanding. Fi is competitive among all open-sourced models at around 9B parameters. Fi-9B is good at both factual tasks and preferred by LLM-judges.
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### Fact-based Evaluation (Open LLM Leaderboard)
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| **Metric** | **winogrande** | **hellaswag** | **truthfulqa** | **ai2_arc** |
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|-----------------|----------------|---------------|----------------|-------------|
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| **Yi-9B-200K** | 71.67 | 56.72 | 33.80 | 69.25 |
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| **Fi-9B-200K** | 71.11 | **57.28** | **40.86** | **72.58** |
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### Long-context Modeling (LongBench)
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| **Name** | **Average_zh** | **Average_en** | **Code Completion** |
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|----------------|----------------|----------------|---------------------|
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| **Yi-9B-200K** | 30.288 | 36.7071 | 72.2 |
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| **Fi-9B-200K** | **41.092** | **40.9536** | 46.0 |
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<details>
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<summary>Score breakdown</summary>
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| **Name** | **Few-shot Learning_en** | **Synthetic Tasks_en** | **Single-Doc QA_en** | **Multi-Doc QA_en** | **Summarization_en** | **Few-shot Learning_zh** | **Synthetic Tasks_zh** | **Single-Doc QA_zh** | **Multi-Doc QA_zh** | **Summarization_zh** |
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|----------------|--------------------------|------------------------|----------------------|---------------------|----------------------|--------------------------|------------------------|----------------------|---------------------|----------------------|
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| **Yi-9B-200K** | 60.6 | 22.8 | 30.9 | 38.9 | 25.8 | 46.5 | 28.0 | 49.6 | 17.7 | 9.7 |
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| **Fi-9B-200K** | **63.8** | **40.2** | **36.2** | 38.0 | **26.3** | 30.0 | **75.1** | **55.6** | **30.7** | **14.1** |
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</details>
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<!--### Performance on Preference TODO-->
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### Bilingual Ability (CMMLU & MMLU)
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| **Name** | **CMMLU** |
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|----------------|-----------|
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| **Yi-9B-200K** | 71.97 |
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| **Fi-9B-200K** | 73.28 |
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## How to use Fi
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## Current Limitations
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- This version of Fi-9B may not be able to stop generation in some scenarios. I will fix that soon.
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- Compared to the original Yi-9B-200K, Fi-9B has degraded ability for code completion. This may be due to the lack of raw code data during instruction tuning.
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