From 5d5e96b6f3032698ae17a6a46e927ab20fb5e3d0 Mon Sep 17 00:00:00 2001 From: Jintao Huang Date: Wed, 31 Jul 2024 14:26:25 +0800 Subject: [PATCH 1/3] update docs & model --- README.md | 5 +- README_CN.md | 5 +- ...14\346\225\260\346\215\256\351\233\206.md" | 4 ++ .../LLM/Supported-models-datasets.md | 4 ++ swift/llm/utils/model.py | 46 +++++++++++++++++++ 5 files changed, 60 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 4dbfe21ea..fe57fd5d5 100644 --- a/README.md +++ b/README.md @@ -55,6 +55,7 @@ You can contact us and communicate with us by adding our group: | ## 🎉 News +- 2024.07.31: Supports internlm2.5 series of 1.8b and 20b. Experience it using swift infer --model_type internlm2_5-1_8b-chat. - 🔥2024.07.29: Support the use of lmdeploy for inference acceleration of LLM and VLM models. Documentation can be found [here](docs/source_en/Multi-Modal/LmDeploy-inference-acceleration.md). - 🔥2024.07.24: Support DPO/ORPO/SimPO/CPO alignment algorithm for vision MLLM, training scripts can be find in [Document](docs/source_en/Multi-Modal/human-preference-alignment-training-documentation.md). support RLAIF-V dataset. - 🔥2024.07.24: Support using Megatron for CPT and SFT on the Qwen2 series. You can refer to the [Megatron training documentation](docs/source_en/LLM/Megatron-training.md). @@ -73,6 +74,8 @@ You can contact us and communicate with us by adding our group: - 2024.07.02: Support for using vLLM for accelerating inference and deployment of multimodal large models such as the llava series and phi3-vision models. You can refer to the [Multimodal & vLLM Inference Acceleration Documentation](docs/source_en/Multi-Modal/vllm-inference-acceleration.md) for more information. - 2024.07.02: Support for `llava1_6-vicuna-7b-instruct`, `llava1_6-vicuna-13b-instruct` and other llava-hf models. For best practices, refer to [here](docs/source_en/Multi-Modal/llava-best-practice.md). - 🔥2024.06.29: Support [eval-scope](https://github.com/modelscope/eval-scope)&[open-compass](https://github.com/open-compass/opencompass) for evaluation! Now we have supported over 50 eval datasets like `BoolQ, ocnli, humaneval, math, ceval, mmlu, gsk8k, ARC_e`, please check our [Eval Doc](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/LLM-eval.md) to begin! Next sprint we will support Multi-modal and Agent evaluation, remember to follow us : ) +
More + - 🔥2024.06.28: Support for **Florence** series model! See [document](docs/source_en/Multi-Modal/florence-best-pratice.md) - 🔥2024.06.28: Support for Gemma2 series models: gemma2-9b, gemma2-9b-instruct, gemma2-27b, gemma2-27b-instruct. - 🔥2024.06.18: Supports **DeepSeek-Coder-v2** series model! Use model_type `deepseek-coder-v2-instruct` and `deepseek-coder-v2-lite-instruct` to begin. @@ -83,8 +86,6 @@ You can contact us and communicate with us by adding our group: - 🔥2024.06.01: Supports **SimPO** training! See [document](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/SimPO.md) to start training! - 🔥2024.06.01: Support for deploying large multimodal models, please refer to the [Multimodal Deployment Documentation](docs/source_en/Multi-Modal/mutlimodal-deployment.md) for more information. - 2024.05.31: Supports Mini-Internvl model, Use model_type `mini-internvl-chat-2b-v1_5` and `mini-internvl-chat-4b-v1_5`to train. -
More - - 2024.05.24: Supports Phi3-vision model, Use model_type `phi3-vision-128k-instruct` to train. - 2024.05.22: Supports DeepSeek-V2-Lite series models, model_type are `deepseek-v2-lite` and `deepseek-v2-lite-chat` - 2024.05.22: Supports TeleChat-12B-v2 model with quantized version, model_type are `telechat-12b-v2` and `telechat-12b-v2-gptq-int4` diff --git a/README_CN.md b/README_CN.md index d8c7c2d56..205adc6e2 100644 --- a/README_CN.md +++ b/README_CN.md @@ -56,6 +56,7 @@ SWIFT具有丰富全面的文档，请查看我们的文档网站: ## 🎉 新闻 +- 2024.07.31: 支持internlm2.5的1.8b和20b系列. 使用`swift infer --model_type internlm2_5-1_8b-chat`进行体验. - 🔥2024.07.29: 支持使用lmdeploy对LLM和VLM模型进行推理加速. 文档可以查看[这里](docs/source/Multi-Modal/LmDeploy推理加速文档.md). - 🔥2024.07.24: 人类偏好对齐算法支持视觉多模态大模型, 包括DPO/ORPO/SimPO/CPO, 训练参考[文档](docs/source/Multi-Modal/人类偏好对齐训练文档.md). 支持数据集RLAIF-V. - 🔥2024.07.24: 支持使用megatron对qwen2系列进行CPT和SFT. 可以查看[megatron训练文档](docs/source/LLM/Megatron训练文档.md). @@ -74,6 +75,8 @@ SWIFT具有丰富全面的文档，请查看我们的文档网站: - 2024.07.02: 支持使用vllm对多模态大模型: llava系列, phi3-vision模型进行推理加速和部署. 可以查看[多模态&vLLM推理加速文档](docs/source/Multi-Modal/vLLM推理加速文档.md)获取更多信息. - 2024.07.02: 支持`llava1_6-vicuna-7b-instruct`, `llava1_6-vicuna-13b-instruct`等llava-hf模型. 最佳实践可以查看[这里](docs/source/Multi-Modal/llava最佳实践.md). - 🔥2024.06.29: 支持[eval-scope](https://github.com/modelscope/eval-scope)&[open-compass](https://github.com/open-compass/opencompass)评测! 我们支持了包含`BoolQ, ocnli, humaneval, math, ceval, mmlu, gsk8k, ARC_e`等50+标准数据集在内的评测流程, 请查看我们的[评测文档](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM评测文档.md)来使用。下个迭代我们会支持多模态评测和Agent评测，记得持续关注我们: ) +
More + - 🔥2024.06.28: 支持**Florence**系列模型: 可以查看[Florence最佳实践](docs/source/Multi-Modal/florence最佳实践.md). - 🔥2024.06.28: 支持**Gemma2**系列模型: gemma2-9b, gemma2-9b-instruct, gemma2-27b, gemma2-27b-instruct. - 🔥2024.06.18: 支持**DeepSeek-Coder-v2**系列模型! 使用model_type`deepseek-coder-v2-instruct`和`deepseek-coder-v2-lite-instruct`来开启训练和推理. @@ -84,8 +87,6 @@ SWIFT具有丰富全面的文档，请查看我们的文档网站: - 🔥2024.06.01: 支持**SimPO**训练，使用`swift simpo`来开始训练，最佳实践可以查看[这里](https://github.com/modelscope/swift/tree/main/docs/source/LLM/SimPO算法最佳实践.md) - 🔥2024.06.01: 支持多模态大模型部署, 可以查看[多模态部署文档](docs/source/Multi-Modal/MLLM部署文档.md). - 2024.05.31: 支持Mini-Internvl多模态模型, 使用model_type `mini-internvl-chat-2b-v1_5`和`mini-internvl-chat-4b-v1_5`来训练. -
更多 - - 2024.05.24: 支持Phi3多模态模型, 使用model_type `phi3-vision-128k-instruct`来训练. - 2024.05.22: 支持DeepSeek-V2-lite系列模型, model_type为 `deepseek-v2-lite`和`deekseek-v2-lite-chat` - 2024.05.22: 支持TeleChat-12b-v2模型和量化版本, model_type为 `telechat-12b-v2`和`telechat-12b-v2-gptq-int4` diff --git "a/docs/source/LLM/\346\224\257\346\214\201\347\232\204\346\250\241\345\236\213\345\222\214\346\225\260\346\215\256\351\233\206.md" "b/docs/source/LLM/\346\224\257\346\214\201\347\232\204\346\250\241\345\236\213\345\222\214\346\225\260\346\215\256\351\233\206.md" index a88c9c506..ce5ee7799 100644 --- "a/docs/source/LLM/\346\224\257\346\214\201\347\232\204\346\250\241\345\236\213\345\222\214\346\225\260\346\215\256\351\233\206.md" +++ "b/docs/source/LLM/\346\224\257\346\214\201\347\232\204\346\250\241\345\236\213\345\222\214\346\225\260\346\215\256\351\233\206.md" @@ -203,9 +203,13 @@ |internlm2-20b|[Shanghai_AI_Laboratory/internlm2-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-20b](https://huggingface.co/internlm/internlm2-20b)| |internlm2-20b-sft-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b-sft](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b-sft/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-chat-20b-sft](https://huggingface.co/internlm/internlm2-chat-20b-sft)| |internlm2-20b-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-chat-20b](https://huggingface.co/internlm/internlm2-chat-20b)| +|internlm2_5-1_8b|[Shanghai_AI_Laboratory/internlm2_5-1_8b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-1_8b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-1_8b](https://huggingface.co/internlm/internlm2_5-1_8b)| +|internlm2_5-1_8b-chat|[Shanghai_AI_Laboratory/internlm2_5-1_8b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-1_8b-chat](https://huggingface.co/internlm/internlm2_5-1_8b-chat)| |internlm2_5-7b|[Shanghai_AI_Laboratory/internlm2_5-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b](https://huggingface.co/internlm/internlm2_5-7b)| |internlm2_5-7b-chat|[Shanghai_AI_Laboratory/internlm2_5-7b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b-chat](https://huggingface.co/internlm/internlm2_5-7b-chat)| |internlm2_5-7b-chat-1m|[Shanghai_AI_Laboratory/internlm2_5-7b-chat-1m](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b-chat-1m/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b-chat-1m](https://huggingface.co/internlm/internlm2_5-7b-chat-1m)| +|internlm2_5-20b|[Shanghai_AI_Laboratory/internlm2_5-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-20b](https://huggingface.co/internlm/internlm2_5-20b)| +|internlm2_5-20b-chat|[Shanghai_AI_Laboratory/internlm2_5-20b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-20b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-20b-chat](https://huggingface.co/internlm/internlm2_5-20b-chat)| |internlm2-math-7b|[Shanghai_AI_Laboratory/internlm2-math-base-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-7b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-base-7b](https://huggingface.co/internlm/internlm2-math-base-7b)| |internlm2-math-7b-chat|[Shanghai_AI_Laboratory/internlm2-math-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-7b/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-7b](https://huggingface.co/internlm/internlm2-math-7b)| |internlm2-math-20b|[Shanghai_AI_Laboratory/internlm2-math-base-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-base-20b](https://huggingface.co/internlm/internlm2-math-base-20b)| diff --git a/docs/source_en/LLM/Supported-models-datasets.md b/docs/source_en/LLM/Supported-models-datasets.md index c4f1a40ba..008ccc47c 100644 --- a/docs/source_en/LLM/Supported-models-datasets.md +++ b/docs/source_en/LLM/Supported-models-datasets.md @@ -203,9 +203,13 @@ The table below introcudes all models supported by SWIFT: |internlm2-20b|[Shanghai_AI_Laboratory/internlm2-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-20b](https://huggingface.co/internlm/internlm2-20b)| |internlm2-20b-sft-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b-sft](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b-sft/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-chat-20b-sft](https://huggingface.co/internlm/internlm2-chat-20b-sft)| |internlm2-20b-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2-chat-20b](https://huggingface.co/internlm/internlm2-chat-20b)| +|internlm2_5-1_8b|[Shanghai_AI_Laboratory/internlm2_5-1_8b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-1_8b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-1_8b](https://huggingface.co/internlm/internlm2_5-1_8b)| +|internlm2_5-1_8b-chat|[Shanghai_AI_Laboratory/internlm2_5-1_8b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-1_8b-chat](https://huggingface.co/internlm/internlm2_5-1_8b-chat)| |internlm2_5-7b|[Shanghai_AI_Laboratory/internlm2_5-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b](https://huggingface.co/internlm/internlm2_5-7b)| |internlm2_5-7b-chat|[Shanghai_AI_Laboratory/internlm2_5-7b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b-chat](https://huggingface.co/internlm/internlm2_5-7b-chat)| |internlm2_5-7b-chat-1m|[Shanghai_AI_Laboratory/internlm2_5-7b-chat-1m](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-7b-chat-1m/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-7b-chat-1m](https://huggingface.co/internlm/internlm2_5-7b-chat-1m)| +|internlm2_5-20b|[Shanghai_AI_Laboratory/internlm2_5-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-20b](https://huggingface.co/internlm/internlm2_5-20b)| +|internlm2_5-20b-chat|[Shanghai_AI_Laboratory/internlm2_5-20b-chat](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2_5-20b-chat/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|-|[internlm/internlm2_5-20b-chat](https://huggingface.co/internlm/internlm2_5-20b-chat)| |internlm2-math-7b|[Shanghai_AI_Laboratory/internlm2-math-base-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-7b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-base-7b](https://huggingface.co/internlm/internlm2-math-base-7b)| |internlm2-math-7b-chat|[Shanghai_AI_Laboratory/internlm2-math-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-7b/summary)|wqkv|internlm2|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-7b](https://huggingface.co/internlm/internlm2-math-7b)| |internlm2-math-20b|[Shanghai_AI_Laboratory/internlm2-math-base-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-20b/summary)|wqkv|default-generation|✔|✔|✔|transformers>=4.38|math|[internlm/internlm2-math-base-20b](https://huggingface.co/internlm/internlm2-math-base-20b)| diff --git a/swift/llm/utils/model.py b/swift/llm/utils/model.py index bfc2b3447..5b105f983 100644 --- a/swift/llm/utils/model.py +++ b/swift/llm/utils/model.py @@ -271,9 +271,13 @@ class ModelType: internlm2_20b_sft_chat = 'internlm2-20b-sft-chat' internlm2_20b_chat = 'internlm2-20b-chat' # internlm2.5 + internlm2_5_1_8b = 'internlm2_5-1_8b' + internlm2_5_1_8b_chat = 'internlm2_5-1_8b-chat' internlm2_5_7b = 'internlm2_5-7b' internlm2_5_7b_chat = 'internlm2_5-7b-chat' internlm2_5_7b_chat_1m = 'internlm2_5-7b-chat-1m' + internlm2_5_20b = 'internlm2_5-20b' + internlm2_5_20b_chat = 'internlm2_5-20b-chat' # internlm2-math internlm2_math_7b = 'internlm2-math-7b' internlm2_math_7b_chat = 'internlm2-math-7b-chat' @@ -3498,6 +3502,27 @@ def get_model_tokenizer_qwen2_intx(model_dir: str, return get_model_tokenizer_qwen_intx(model_dir, torch_dtype, model_kwargs, load_model, **kwargs) +@register_model( + ModelType.internlm2_5_1_8b, + 'Shanghai_AI_Laboratory/internlm2_5-1_8b', + LoRATM.internlm2, + TemplateType.default_generation, + requires=['transformers>=4.38'], + support_flash_attn=True, + support_vllm=True, + support_lmdeploy=True, + hf_model_id='internlm/internlm2_5-1_8b') +@register_model( + ModelType.internlm2_5_1_8b_chat, + 'Shanghai_AI_Laboratory/internlm2_5-1_8b-chat', + LoRATM.internlm2, + TemplateType.internlm2, + eos_token='<|im_end|>', + requires=['transformers>=4.38'], + support_flash_attn=True, + support_vllm=True, + support_lmdeploy=True, + hf_model_id='internlm/internlm2_5-1_8b-chat') @register_model( ModelType.internlm2_5_7b, 'Shanghai_AI_Laboratory/internlm2_5-7b', @@ -3530,6 +3555,27 @@ def get_model_tokenizer_qwen2_intx(model_dir: str, support_vllm=True, support_lmdeploy=True, hf_model_id='internlm/internlm2_5-7b-chat-1m') +@register_model( + ModelType.internlm2_5_20b, + 'Shanghai_AI_Laboratory/internlm2_5-20b', + LoRATM.internlm2, + TemplateType.default_generation, + requires=['transformers>=4.38'], + support_flash_attn=True, + support_vllm=True, + support_lmdeploy=True, + hf_model_id='internlm/internlm2_5-20b') +@register_model( + ModelType.internlm2_5_20b_chat, + 'Shanghai_AI_Laboratory/internlm2_5-20b-chat', + LoRATM.internlm2, + TemplateType.internlm2, + eos_token='<|im_end|>', + requires=['transformers>=4.38'], + support_flash_attn=True, + support_vllm=True, + support_lmdeploy=True, + hf_model_id='internlm/internlm2_5-20b-chat') @register_model( ModelType.internlm2_1_8b, 'Shanghai_AI_Laboratory/internlm2-1_8b', From 7f824bb4d3f273cdbb31270a2a932625b55794a9 Mon Sep 17 00:00:00 2001 From: Jintao Huang Date: Wed, 31 Jul 2024 15:25:27 +0800 Subject: [PATCH 2/3] update --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index fe57fd5d5..1cc642525 100644 --- a/README.md +++ b/README.md @@ -55,7 +55,7 @@ You can contact us and communicate with us by adding our group: | ## 🎉 News -- 2024.07.31: Supports internlm2.5 series of 1.8b and 20b. Experience it using swift infer --model_type internlm2_5-1_8b-chat. +- 2024.07.31: Supports internlm2.5 series of 1.8b and 20b. Experience it using `swift infer --model_type internlm2_5-1_8b-chat`. - 🔥2024.07.29: Support the use of lmdeploy for inference acceleration of LLM and VLM models. Documentation can be found [here](docs/source_en/Multi-Modal/LmDeploy-inference-acceleration.md). - 🔥2024.07.24: Support DPO/ORPO/SimPO/CPO alignment algorithm for vision MLLM, training scripts can be find in [Document](docs/source_en/Multi-Modal/human-preference-alignment-training-documentation.md). support RLAIF-V dataset. - 🔥2024.07.24: Support using Megatron for CPT and SFT on the Qwen2 series. You can refer to the [Megatron training documentation](docs/source_en/LLM/Megatron-training.md). From e9c4923cfa49a26cf5c35e4b6d6d2fadd87a11ac Mon Sep 17 00:00:00 2001 From: Jintao Huang Date: Tue, 6 Aug 2024 10:42:21 +0800 Subject: [PATCH 3/3] update --- README.md | 2 +- README_CN.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 1f8490bc0..88d63908c 100644 --- a/README.md +++ b/README.md @@ -55,7 +55,7 @@ You can contact us and communicate with us by adding our group: | ## 🎉 News -- 2024.08.05: Supports internlm2.5 series of 1.8b and 20b. Experience it using `swift infer --model_type internlm2_5-1_8b-chat`. +- 2024.08.06: Supports internlm2.5 series of 1.8b and 20b. Experience it using `swift infer --model_type internlm2_5-1_8b-chat`. - 🔥2024.08.02: Support Fourier Ft. Use `--sft_type fourierft` to begin, Check parameter documentation [here](https://swift.readthedocs.io/en/latest/LLM/Command-line-parameters.html). - 🔥2024.07.29: Support the use of lmdeploy for inference acceleration of LLM and VLM models. Documentation can be found [here](docs/source_en/Multi-Modal/LmDeploy-inference-acceleration.md). - 🔥2024.07.24: Support DPO/ORPO/SimPO/CPO alignment algorithm for vision MLLM, training scripts can be find in [Document](docs/source_en/Multi-Modal/human-preference-alignment-training-documentation.md). support RLAIF-V dataset. diff --git a/README_CN.md b/README_CN.md index b6694037b..d926167ae 100644 --- a/README_CN.md +++ b/README_CN.md @@ -56,7 +56,7 @@ SWIFT具有丰富全面的文档，请查看我们的文档网站: ## 🎉 新闻 -- 2024.08.05: 支持internlm2.5的1.8b和20b系列. 使用`swift infer --model_type internlm2_5-1_8b-chat`进行体验. +- 2024.08.06: 支持internlm2.5的1.8b和20b系列. 使用`swift infer --model_type internlm2_5-1_8b-chat`进行体验. - 🔥2024.08.02: 支持Fourier Ft训练. 使用方式为`--sft_type fourierft`, 参数可以参考[这里](https://swift.readthedocs.io/zh-cn/latest/LLM/%E5%91%BD%E4%BB%A4%E8%A1%8C%E5%8F%82%E6%95%B0.html). - 🔥2024.07.29: 支持使用lmdeploy对LLM和VLM模型进行推理加速. 文档可以查看[这里](docs/source/Multi-Modal/LmDeploy推理加速文档.md). - 🔥2024.07.24: 人类偏好对齐算法支持视觉多模态大模型, 包括DPO/ORPO/SimPO/CPO, 训练参考[文档](docs/source/Multi-Modal/人类偏好对齐训练文档.md). 支持数据集RLAIF-V.