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@ -267,12 +267,13 @@ streamlit run fast_inference.py
### 数据集下载地址
| MiniMind训练数据集 | 下载地址 |
|------------------|---------------------------------------------------------------------------------------------------------------|
| **【Pretrain数据】** | [seq-monkey通用文本数据集](http://share.mobvoi.com:5000/sharing/O91blwPkY) |
| **【SFT数据】** | [匠数大模型SFT数据集](https://www.modelscope.cn/datasets/deepctrl/deepctrl-sft-data/resolve/master/sft_data_zh.jsonl) |
| **【DPO数据】** | [活字数据集1](https://huggingface.co/datasets/Skepsun/huozi_rlhf_data_json) |
| **【DPO数据】** | [活字数据集2](https://huggingface.co/datasets/beyond/rlhf-reward-single-round-trans_chinese) |
| MiniMind训练数据集 | 下载地址 |
|--------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------|
| **【tokenizer训练集】** | [HuggingFace](https://huggingface.co/datasets/jingyaogong/minimind_dataset/tree/main) / [百度网盘](https://pan.baidu.com/s/1yAw1LVTftuhQGAC1Y9RdYQ?pwd=6666) |
| **【Pretrain数据】** | [seq-monkey通用文本数据集](http://share.mobvoi.com:5000/sharing/O91blwPkY) |
| **【SFT数据】** | [匠数大模型SFT数据集](https://www.modelscope.cn/datasets/deepctrl/deepctrl-sft-data/resolve/master/sft_data_zh.jsonl) |
| **【DPO数据】** | [活字数据集1](https://huggingface.co/datasets/Skepsun/huozi_rlhf_data_json) |
| **【DPO数据】** | [活字数据集2](https://huggingface.co/datasets/beyond/rlhf-reward-single-round-trans_chinese) |
# 📌 Model

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@ -245,7 +245,7 @@ git clone https://github.com/jingyaogong/minimind.git
sizes:
| Tokenizer Model | Vocabulary Size | Source |
|----------------------|------------------|-----------------------|
|----------------------|------------------|-----------------------|
| yi tokenizer | 64,000 | 01-AI (China) |
| qwen2 tokenizer | 151,643 | Alibaba Cloud (China) |
| glm tokenizer | 151,329 | Zhipu AI (China) |
@ -304,12 +304,13 @@ git clone https://github.com/jingyaogong/minimind.git
### Dataset Download Links
| MiniMind Training Dataset | Download Link |
|---------------------------|------------------------------------------------------------------------------------------------------------------------------------|
| **[Pretrain Data]** | [Seq-Monkey General Text Dataset](http://share.mobvoi.com:5000/sharing/O91blwPkY) |
| **[SFT Data]** | [Jiangshu Large Model SFT Dataset](https://www.modelscope.cn/datasets/deepctrl/deepctrl-sft-data/resolve/master/sft_data_zh.jsonl) |
| **[DPO Data]** | [Huozi Dataset 1](https://huggingface.co/datasets/Skepsun/huozi_rlhf_data_json) |
| **[DPO Data]** | [Huozi Dataset 2](https://huggingface.co/datasets/beyond/rlhf-reward-single-round-trans_chinese) |
| MiniMind Training Dataset | Download Link |
|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
| **[tokenizer Data]** | [HuggingFace](https://huggingface.co/datasets/jingyaogong/minimind_dataset/tree/main) / [Baidu](https://pan.baidu.com/s/1yAw1LVTftuhQGAC1Y9RdYQ?pwd=6666) |
| **[Pretrain Data]** | [Seq-Monkey General Text Dataset](http://share.mobvoi.com:5000/sharing/O91blwPkY) |
| **[SFT Data]** | [Jiangshu Large Model SFT Dataset](https://www.modelscope.cn/datasets/deepctrl/deepctrl-sft-data/resolve/master/sft_data_zh.jsonl) |
| **[DPO Data]** | [Huozi Dataset 1](https://huggingface.co/datasets/Skepsun/huozi_rlhf_data_json) |
| **[DPO Data]** | [Huozi Dataset 2](https://huggingface.co/datasets/beyond/rlhf-reward-single-round-trans_chinese) |
# 📌 Model
@ -430,12 +431,12 @@ Environment: python 3.9 + Torch 2.1.2 + DDP multi-GPU training
---
🔗 **Trained Model Weights**:
| Model Name | params | Config | pretrain_model | single_sft_model | multi_sft_model |
|------------------|--------|-------------------------------------------------|----------------------------------------------------------------|----------------------------------------------------------------|----------------------------------------------------------------|
| minimind-small-T | 26M | d_model=512<br/>n_layers=8 | - | [链接](https://pan.baidu.com/s/1_COe0FQRDmeapSsvArahCA?pwd=6666) | [链接](https://pan.baidu.com/s/1GsGsWSL0Dckl0YPRXiBIFQ?pwd=6666) |
| minimind-small | 56M | d_model=640<br/>n_layers=8 | [链接](https://pan.baidu.com/s/1nJuOpnu5115FDuz6Ewbeqg?pwd=6666) | [链接](https://pan.baidu.com/s/1lRX0IcpjNFSySioeCfifRQ?pwd=6666) | [链接](https://pan.baidu.com/s/1LzVxBpL0phtGUH267Undqw?pwd=6666) |
| minimind | 218M | d_model=1024<br/>n_layers=16 | [链接](https://pan.baidu.com/s/1jzA7uLEi-Jen2fW5olCmEg?pwd=6666) | [链接](https://pan.baidu.com/s/1Hvt0Q_UB_uW2sWTw6w1zRQ?pwd=6666) | [链接](https://pan.baidu.com/s/1fau9eat3lXilnrG3XNhG5Q?pwd=6666) |
| minimind-MoE | 166M | d_model=1024<br/>n_layers=8<br/>share+route=2+4 | [链接](https://pan.baidu.com/s/11CneDVTkw2Y6lNilQX5bWw?pwd=6666) | [链接](https://pan.baidu.com/s/1fRq4MHZec3z-oLK6sCzj_A?pwd=6666) | [链接](https://pan.baidu.com/s/1HC2KSM_-RHRtgv7ZDkKI9Q?pwd=6666) |
| Model Name | params | Config | pretrain_model | single_sft_model | multi_sft_model |
|------------------|--------|-------------------------------------------------|-----------------------------------------------------------------|-----------------------------------------------------------------|-----------------------------------------------------------------|
| minimind-small-T | 26M | d_model=512<br/>n_layers=8 | - | [URL](https://pan.baidu.com/s/1_COe0FQRDmeapSsvArahCA?pwd=6666) | [URL](https://pan.baidu.com/s/1GsGsWSL0Dckl0YPRXiBIFQ?pwd=6666) |
| minimind-small | 56M | d_model=640<br/>n_layers=8 | [URL](https://pan.baidu.com/s/1nJuOpnu5115FDuz6Ewbeqg?pwd=6666) | [URL](https://pan.baidu.com/s/1lRX0IcpjNFSySioeCfifRQ?pwd=6666) | [URL](https://pan.baidu.com/s/1LzVxBpL0phtGUH267Undqw?pwd=6666) |
| minimind | 218M | d_model=1024<br/>n_layers=16 | [URL](https://pan.baidu.com/s/1jzA7uLEi-Jen2fW5olCmEg?pwd=6666) | [URL](https://pan.baidu.com/s/1Hvt0Q_UB_uW2sWTw6w1zRQ?pwd=6666) | [URL](https://pan.baidu.com/s/1fau9eat3lXilnrG3XNhG5Q?pwd=6666) |
| minimind-MoE | 166M | d_model=1024<br/>n_layers=8<br/>share+route=2+4 | [URL](https://pan.baidu.com/s/11CneDVTkw2Y6lNilQX5bWw?pwd=6666) | [URL](https://pan.baidu.com/s/1fRq4MHZec3z-oLK6sCzj_A?pwd=6666) | [URL](https://pan.baidu.com/s/1HC2KSM_-RHRtgv7ZDkKI9Q?pwd=6666) |
---
@ -603,9 +604,9 @@ and provide ratings and rankings.
### Ranking (from highest to lowest):
| 模型 | D模型 | A模型 | B模型 | F模型 | C模型 | E模型 |
|----|-----|-----|-----|-----|-----|-----|
| 分数 | 85 | 80 | 75 | 60 | 55 | 50 |
| Model | D Model | A Model | B Model | F Model | C Model | E Model |
|-------|---------|---------|---------|---------|---------|---------|
| Score | 85 | 80 | 75 | 60 | 55 | 50 |
These scores and rankings are based on each model’s overall performance in accuracy, clarity, and completeness.