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Breeze-7B-Instruct-v0_1

Text Generation
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PyTorch
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mistral
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Inference Endpoints
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@@ -28,46 +28,42 @@ and is comparable with Mistral-7B-Instruct-v0.1 on MMLU and MT-Bench in English.
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  ## Base Model Performance
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- | Models | | TMMLU+ (ACC) | DRCD (EM) | MMLU (ACC) |
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- |---------------------------------------------|--------|--------------|-----------|------------|
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- | | |TC, Knowledge |TC, Reasoning|EN, Knowledge|
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- | | | 5 shot | 3 shot | 5 shot |
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- | 01-ai/Yi-6B | 6B | 49.63 | 76.61 | 65.35 |
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- | MediaTek-Research/Breeze-7B-Base-v0.1 | 7B | 40.35 | 81.13 | 61.63 |
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- | mistralai/Mistral-7B-v0.1 | 7B | 36.93 | 79.27 | 64.89 |
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- | Qwen/Qwen-7B | 7B | 42.84 | 0.0 * | 61.00 |
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- | Qwen/Qwen-14B | 14B | 51.30 | 16.95 * | 68.83 |
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- | 01-ai/Yi-34B | 34B | 63.10 | 84.57 | 77.42 |
 
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  \* Few-shot learning cannot effectively guide the model to generate the proper answer.
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- | Category ACC of TMMLU+ | STEM | Social Science | Humanities | Other |
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  |-----------------------------------------------------|--------------|----------------|------------|------------|
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- | 01-ai/Yi-6B | 41.14 | 57.77 | 50.22 | 49.39 |
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- | MediaTek-Research/Breeze-7B-Base-v0.1 | 35.74 | 46.08 | 40.29 | 39.27 |
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- | mistralai/Mistral-7B-v0.1 | 33.01 | 42.23 | 35.86 | 37.63 |
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- | Qwen/Qwen-7B | 28.25 | 47.80 | 43.14 | 42.17 |
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- | Qwen/Qwen-14B | 46.51 | 58.20 | 51.12 | 49.38 |
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- | 01-ai/Yi-34B | 56.03 | 73.06 | 61.12 | 62.19 |
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  ## Inference Performance
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- | Models | Speed (char/sec) |Estimated Max Input Length (TC Char)|
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  |--------------------------------------------------------------------|-------------------|--------------------------|
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- | MediaTek-Research/Breeze-7B-Base-v0.1 | 59.57 | 10.1k |
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- | mistralai/Mistral-7B-v0.1 | 45.31 | 6.3k |
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- | yentinglin/Taiwan-LLM-7B-v2.1-base | 16.23 | 2.6k |
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- | yentinglin/Taiwan-LLM-13B-v2.0-base | 19.61 | 2.6k |
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- | 01-ai/Yi-6B | 62.08 | 4.4k |
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- | 01-ai/Yi-34B | 15.18 | 4.4k |
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- | Qwen/Qwen-7B | 55.00 | 9.7k |
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- | Qwen/Qwen-14B | 51.12 | 9.7k |
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-
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- \*Test Input: 201802最高法院民事裁判書(first 1500 characters)
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- \*Test Prompt: 請重新寫出這篇文章
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- \*Output Token: 1000 (We set max_tokens=400 for Qwen/Qwen-7B)
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- \*Using vllm, TP=2 on 2 A6000
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  ## Chat Model Performance
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@@ -75,27 +71,28 @@ and is comparable with Mistral-7B-Instruct-v0.1 on MMLU and MT-Bench in English.
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  |--------------------------------------------|--------|--------------|--------------|-----------|---------------------|------------|------------|------------------|
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  | | |TC, Knowledge |TC, Knowledge |TC, Reasoning|TC, Chat |EN, Knowledge|EN, Knowledge|EN, Chat |
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  | | | 0 shot | 5 shot | 3 shot | 0 shot | 0 shot | 5 shot | 0 shot |
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- | 01-ai/Yi-6B-Chat | 6B | 44.79 | | | 5.0 | 59.45 | | 6.0 |
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- | MediaTek-Research/Breeze-7B-Instruct-v0.1 | 7B | 41.61 | | | 5.7 | 63.26 | | 7.1 |
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- | MediaTek-Research/Breeze-7B-Instruct-64k-v0.1| 7B | 40.99 | | | | 63.68 | | 7.1 |
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- | yentinglin/Taiwan-LLM-7B-v2.1-chat | 7B | 28.08 | | | 4.2 | 42.72 | | -* |
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- | Qwen/Qwen-7B-Chat | 7B | 40.02 | | | 5.4 | 55.94 | | 6.2 |
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- | yentinglin/Taiwan-LLM-13B-v2.0-chat | 13B | 29.47 | | | 5.0 | 50.50 | | -* |
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- | Qwen/Qwen-14B-Chat | 14B | 48.41 | | | 6.4 | 64.91 | | 7.2 |
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- | 01-ai/Yi-34B-Chat | 34B | 54.87 | | | 6.9 | 71.04 | | 7.6 |
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  | gpt-3.5-turbo-1106 | | | | 76.30 | 7.1 | | | 7.9 |
 
 
 
 
 
 
 
 
 
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  \* Taiwan-LLM models responds to multi-turn questions (English) in Traditional Chinese.
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  | Category ACC of TMMLU+ | STEM | Social Science | Humanities | Other |
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  |-----------------------------------------------------|--------------|----------------|------------|------------|
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- | 01-ai/Yi-6B-Chat | 26.28 | 33.48 | 29.48 | 27.62 |
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- | MediaTek-Research/Breeze-7B-Instruct-v0.1 | 37.45 | 48.35 | 40.26 | 40.44 |
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- | yentinglin/Taiwan-LLM-7B-v2.1-chat | 26.53 | 29.47 | 26.11 | 26.90 |
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- | Qwen/Qwen-7B-Chat | 32.89 | 44.26 | 38.21 | 37.83 |
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- | yentinglin/Taiwan-LLM-13B-v2.0-chat | 29.68 | 37.13 | 30.31 | 30.55 |
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- | Qwen/Qwen-14B-Chat | 46.51 | 58.20 | 51.12 | 49.38 |
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- | 01-ai/Yi-34B-Chat | 46.36 | 65.02 | 52.84 | 52.21 |
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  | gpt-3.5-turbo-1106 | | | | |
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  ## Examples
 
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  ## Base Model Performance
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+ | Models | | TMMLU+ (ACC) | DRCD (EM) | MMLU (ACC) |
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+ |----------------------------------------------|--------|--------------|-------------|------------|
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+ | | |TC, Knowledge |TC, Reasoning|EN, Knowledge|
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+ | | | 5 shot | 3 shot | 5 shot |
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+ | [Yi-34B](https://huggingface.co/01-ai/Yi-34B)| 34B | 63.10 | 84.57 | 77.42 |
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+ | [Qwen-14B](https://huggingface.co/01-ai/Qwen/Qwen-14B)| 14B | 51.30 | 16.95 * | 68.83 |
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+ | [Yi-6B](https://huggingface.co/01-ai/Yi-6B) | 6B | 49.63 | 76.61 | 65.35 |
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+ | [Qwen-7B](https://huggingface.co/01-ai/Qwen/Qwen-7B)| 7B | 42.84 | 0.0 * | 61.00 |
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+ | [Breeze-7B-Base-v0.1](https://huggingface.co/MediaTek-Research/Breeze-7B-Base-v0.1) | 7B | 40.35 | 81.13 | 61.63 |
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+ | [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)| 7B | 36.93 | 79.27 | 64.89 |
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+
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  \* Few-shot learning cannot effectively guide the model to generate the proper answer.
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+ | Category ACC of TMMLU+ (5 shot) | STEM | Social Science | Humanities | Other |
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  |-----------------------------------------------------|--------------|----------------|------------|------------|
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+ | Yi-34B | 56.03 | 73.06 | 61.12 | 62.19 |
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+ | Qwen-14B | 46.51 | 58.20 | 51.12 | 49.38 |
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+ | Yi-6B | 41.14 | 57.77 | 50.22 | 49.39 |
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+ | Qwen-7B | 28.25 | 47.80 | 43.14 | 42.17 |
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+ | Breeze-7B-Base-v0.1 | 35.74 | 46.08 | 40.29 | 39.27 |
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+ | Mistral-7B-v0.1 | 33.01 | 42.23 | 35.86 | 37.63 |
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  ## Inference Performance
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+ | Models | Speed (char/sec) |Max Input Length (TC Char)|
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  |--------------------------------------------------------------------|-------------------|--------------------------|
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+ | Breeze-7B-Base-v0.1 | | |
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+ | Mistral-7B-v0.1 | | |
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+ | Taiwan-LLM-7B-v2.1-base | | |
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+ | Taiwan-LLM-13B-v2.0-base | | |
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+ | Yi-6B | | |
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+ | Yi-34B | | |
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+ | Qwen-7B | | |
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+ | Qwen-14B | | |
 
 
 
 
 
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  ## Chat Model Performance
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  |--------------------------------------------|--------|--------------|--------------|-----------|---------------------|------------|------------|------------------|
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  | | |TC, Knowledge |TC, Knowledge |TC, Reasoning|TC, Chat |EN, Knowledge|EN, Knowledge|EN, Chat |
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  | | | 0 shot | 5 shot | 3 shot | 0 shot | 0 shot | 5 shot | 0 shot |
 
 
 
 
 
 
 
 
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  | gpt-3.5-turbo-1106 | | | | 76.30 | 7.1 | | | 7.9 |
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+ | [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat)| 34B | 54.87 | | | 6.9 | 71.04 | | 7.6 |
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+ | [Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat)| 14B | 48.41 | | | 6.4 | 64.91 | | 7.2 |
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+ | [Yi-6B](https://huggingface.co/01-ai/Yi-6B)| 6B | 44.79 | | | 5.0 | 59.45 | | 6.0 |
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+ | [Breeze-7B-Instruct-v0.1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0.1)| 7B | 41.61 | | | 5.7 | 63.26 | | 7.1 |
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+ | [Breeze-7B-Instruct-64k-v0.1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-64k-v0.1)| 7B | 40.99 | | | | 63.68 | | 7.1 |
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+ | [Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) | 7B | 40.02 | | | 5.4 | 55.94 | | 6.2 |
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+ | [Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) | 13B | 29.47 | | | 5.0 | 50.50 | | -* |
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+ | [Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) | 7B | 28.08 | | | 4.2 | 42.72 | | -* |
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+
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  \* Taiwan-LLM models responds to multi-turn questions (English) in Traditional Chinese.
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  | Category ACC of TMMLU+ | STEM | Social Science | Humanities | Other |
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  |-----------------------------------------------------|--------------|----------------|------------|------------|
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+ | Yi-6B-Chat | 26.28 | 33.48 | 29.48 | 27.62 |
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+ | Breeze-7B-Instruct-v0.1 | 37.45 | 48.35 | 40.26 | 40.44 |
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+ | Taiwan-LLM-7B-v2.1-chat | 26.53 | 29.47 | 26.11 | 26.90 |
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+ | Qwen-7B-Chat | 32.89 | 44.26 | 38.21 | 37.83 |
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+ | Taiwan-LLM-13B-v2.0-chat | 29.68 | 37.13 | 30.31 | 30.55 |
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+ | Qwen-14B-Chat | 46.51 | 58.20 | 51.12 | 49.38 |
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+ | Yi-34B-Chat | 46.36 | 65.02 | 52.84 | 52.21 |
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  | gpt-3.5-turbo-1106 | | | | |
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  ## Examples