[Docs] add InternLM2 model cards (#596)

* [Docs] update InternLM2 model cards * [Docs] update model cards * [Docs] update InternLM2 model cards
2024-01-17 12:24:08 +08:00 · 2024-01-17 12:24:08 +08:00 · 63aa7fe2fa
parent d163169143
commit 63aa7fe2fa
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--- a/model_cards/internlm2_20b.md
+++ b/model_cards/internlm2_20b.md
@ -0,0 +1,42 @@
+# InternLM2-20B Model Card
+
+## Introduction
+
+The second generation of the InternLM model, InternLM2, includes models at two scales: 7B and 20B. For the convenience of users and researchers, we have open-sourced four versions of each scale of the model, which are:
+
+- internlm2-base-20b: A high-quality and highly adaptable model base, serving as an excellent starting point for deep domain adaptation.
+- internlm2-20b (**recommended**): Built upon the internlm2-base, this version has been enhanced in multiple capability directions. It shows outstanding performance in evaluations while maintaining robust general language abilities, making it our recommended choice for most applications.
+- internlm2-chat-20b-sft: Based on the Base model, it undergoes supervised human alignment training.
+- internlm2-chat-20b (**recommended**): Optimized for conversational interaction on top of the internlm2-sft through RLHF, it excels in instruction adherence, empathetic chatting, and tool invocation.
+
+The base model of InternLM2 has the following technical features:
+
+- Effective support for ultra-long contexts of up to 200,000 characters: The model nearly perfectly achieves "finding a needle in a haystack" in long inputs of 200,000 characters. It also leads among open-source models in performance on long-text tasks such as LongBench and L-Eval.
+- Comprehensive performance enhancement: Compared to the previous generation model, it shows significant improvements in various capabilities, including reasoning, mathematics, and coding.
+
+## Model Zoo
+
+| Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | Release Date |
+|---------------------------|------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|
+| **InternLM2 Base 20B** | [🤗internlm/internlm2-base-20b](https://huggingface.co/internlm/internlm2-base-20b) | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-base-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-base-20b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-20b) | 2024-01-17 |
+| **InternLM2 20B** | [🤗internlm/internlm2-20b](https://huggingface.co/internlm/internlm2-20b) | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-20b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-20b) | 2024-01-17 |
+| **InternLM2 Chat 20B SFT**     | [🤗internlm/internlm2-chat-20b-sft](https://huggingface.co/internlm/internlm2-chat-20b-sft)         | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-chat-20b-sft](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b-sft/summary)         | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-20b-sft)     | 2024-01-17   |
+| **InternLM2 Chat 20B**     | [🤗internlm/internlm2-chat-20b](https://huggingface.co/internlm/internlm2-chat-20b)         | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b/summary)         | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-20b)     | 2024-01-17   |
+
+## Performance Evaluation
+
+We have evaluated InternLM2 on several important benchmarks using the open-source evaluation tool [OpenCompass](https://github.com/open-compass/opencompass). Some of the evaluation results are shown in the table below. You are welcome to visit the [OpenCompass Leaderboard](https://opencompass.org.cn/rank) for more evaluation results.
+
+| Dataset\Models | InternLM2-7B | InternLM2-Chat-7B | InternLM2-20B | InternLM2-Chat-20B | ChatGPT | GPT-4 |
+| --- | --- | --- | --- | --- | --- | --- |
+| MMLU | 65.8 | 63.7 | 67.7 | 66.5 | 69.1 | 83.0 |
+| AGIEval | 49.9 | 47.2 | 53.0 | 50.3 | 39.9 | 55.1 |
+| BBH | 65.0 | 61.2 | 72.1 | 68.3 | 70.1 | 86.7 |
+| GSM8K | 70.8 | 70.7 | 76.1 | 79.6 | 78.2 | 91.4 |
+| MATH | 20.2 | 23.0 | 25.5 | 31.9 | 28.0 | 45.8 |
+| HumanEval | 43.3 | 59.8 | 48.8 | 67.1 | 73.2 | 74.4 |
+| MBPP(Sanitized) | 51.8 | 51.4 | 63.0 | 65.8 | 78.9 | 79.0 |
+
+
+- The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass). 
+- The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass).
--- a/model_cards/internlm2_7b.md
+++ b/model_cards/internlm2_7b.md
@ -0,0 +1,42 @@
+# InternLM2-7B Model Card
+
+## Introduction
+
+The second generation of the InternLM model, InternLM2, includes models at two scales: 7B and 20B. For the convenience of users and researchers, we have open-sourced four versions of each scale of the model, which are:
+
+- internlm2-base-7b: A high-quality and highly adaptable model base, serving as an excellent starting point for deep domain adaptation.
+- internlm2-7b (**recommended**): Built upon the internlm2-base, this version has been enhanced in multiple capability directions. It shows outstanding performance in evaluations while maintaining robust general language abilities, making it our recommended choice for most applications.
+- internlm2-chat-7b-sft: Based on the Base model, it undergoes supervised human alignment training.
+- internlm2-chat-7b (**recommended**): Optimized for conversational interaction on top of the internlm2-sft through RLHF, it excels in instruction adherence, empathetic chatting, and tool invocation.
+
+The base model of InternLM2 has the following technical features:
+
+- Effective support for ultra-long contexts of up to 200,000 characters: The model nearly perfectly achieves "finding a needle in a haystack" in long inputs of 200,000 characters. It also leads among open-source models in performance on long-text tasks such as LongBench and L-Eval.
+- Comprehensive performance enhancement: Compared to the previous generation model, it shows significant improvements in various capabilities, including reasoning, mathematics, and coding.
+
+## Model Zoo
+
+| Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | Release Date |
+|---------------------------|------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|
+| **InternLM2 Base 7B**           | [🤗internlm/internlm2-base-7b](https://huggingface.co/internlm/internlm2-base-7b)                     | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-base-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-base-7b/summary)                     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-7b)           |  2024-01-17   |
+| **InternLM2 7B**           | [🤗internlm/internlm2-7b](https://huggingface.co/internlm/internlm2-7b)                     | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-7b/summary)                     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-7b)           |  2024-01-17   |
+| **InternLM2 Chat 7B SFT**      | [🤗internlm/internlm2-chat-7b-sft](https://huggingface.co/internlm/internlm2-chat-7b-sft)           | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-chat-7b-sft](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-7b-sft/summary)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-7b-sft)      | 2024-01-17  |
+| **InternLM2 Chat 7B**      | [🤗internlm/internlm2-chat-7b](https://huggingface.co/internlm/internlm2-chat-7b)           | [<img src="../assets/modelscope_logo.png" width="20px" /> internlm2-chat-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-7b/summary)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-7b)      | 2024-01-17  |
+
+## Performance Evaluation
+
+We have evaluated InternLM2 on several important benchmarks using the open-source evaluation tool [OpenCompass](https://github.com/open-compass/opencompass). Some of the evaluation results are shown in the table below. You are welcome to visit the [OpenCompass Leaderboard](https://opencompass.org.cn/rank) for more evaluation results.
+
+| Dataset\Models | InternLM2-7B | InternLM2-Chat-7B | InternLM2-20B | InternLM2-Chat-20B | ChatGPT | GPT-4 |
+| --- | --- | --- | --- | --- | --- | --- |
+| MMLU | 65.8 | 63.7 | 67.7 | 66.5 | 69.1 | 83.0 |
+| AGIEval | 49.9 | 47.2 | 53.0 | 50.3 | 39.9 | 55.1 |
+| BBH | 65.0 | 61.2 | 72.1 | 68.3 | 70.1 | 86.7 |
+| GSM8K | 70.8 | 70.7 | 76.1 | 79.6 | 78.2 | 91.4 |
+| MATH | 20.2 | 23.0 | 25.5 | 31.9 | 28.0 | 45.8 |
+| HumanEval | 43.3 | 59.8 | 48.8 | 67.1 | 73.2 | 74.4 |
+| MBPP(Sanitized) | 51.8 | 51.4 | 63.0 | 65.8 | 78.9 | 79.0 |
+
+
+- The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass). 
+- The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass).
--- a/model_cards/internlm_20b.md
+++ b/model_cards/internlm_20b.md
@ -15,8 +15,8 @@ In terms of model structure, InternLM-20B opted for a deeper architecture, with

 | Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | OpenXLab(Original) | Release Date |
 |---------------------------|------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|
-| **InternLM Chat 20B**     | [🤗internlm/internlm-chat-20b](https://huggingface.co/internlm/internlm-20b-chat)         | [<img src="./docs/imgs/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-20b-chat/summary)         | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-20b)     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-20b-original)     | 2023-12-12   |
-| **InternLM 20B** | [🤗internlm/internlm-20b](https://huggingface.co/internlm/internlm-20b) | [<img src="./docs/imgs/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-20b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-20b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-20b-original) | 2023-09-20 |
+| **InternLM Chat 20B**     | [🤗internlm/internlm-chat-20b](https://huggingface.co/internlm/internlm-20b-chat)         | [<img src="../assets/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-20b-chat/summary)         | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-20b)     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-20b-original)     | 2023-12-12   |
+| **InternLM 20B** | [🤗internlm/internlm-20b](https://huggingface.co/internlm/internlm-20b) | [<img src="../assets/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-20b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-20b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-20b-original) | 2023-09-20 |

 ## Performance Evaluation

--- a/model_cards/internlm_7b.md
+++ b/model_cards/internlm_7b.md
@ -12,8 +12,8 @@ InternLM-7B contains a 7 billion parameter base model and a chat model tailored

 | Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | OpenXLab(Original) | Release Date |
 |---------------------------|------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|
-| **InternLM Chat 7B**      | [🤗internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)           | [<img src="./docs/imgs/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-chat-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-chat-7b/summary)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b)      | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-original)      | 2023-12-12   |
-| **InternLM 7B**           | [🤗internlm/internlm-7b](https://huggingface.co/internlm/internlm-7b)                     | [<img src="./docs/imgs/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-7b/summary)                     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b-original)           | 2023-07-06   |
+| **InternLM Chat 7B**      | [🤗internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)           | [<img src="../assets/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-chat-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-chat-7b/summary)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b)      | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-original)      | 2023-12-12   |
+| **InternLM 7B**           | [🤗internlm/internlm-7b](https://huggingface.co/internlm/internlm-7b)                     | [<img src="../assets/modelscope_logo.png" width="20px" /> Shanghai_AI_Laboratory/internlm-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-7b/summary)                     | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b)           | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b-original)           | 2023-07-06   |

 ## Performance Evaluation