[feat] update readme

pull/107/head
jingyaogong 2025-11-11 11:12:09 +08:00
parent 92ca9959bb
commit d698d98dc5
2 changed files with 6 additions and 6 deletions

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@ -232,7 +232,7 @@ unzip sft_images.zip && rm sft_images.zip
```bash ```bash
# 基础训练命令(从LLM权重开始,仅训练vision_proj) # 基础训练命令(从LLM权重开始,仅训练vision_proj)
python trainer/train_pretrain_vlm.py --epochs 4 --from_weight llm python train_pretrain_vlm.py --epochs 4 --from_weight llm
``` ```
> 执行预训练,得到 `pretrain_vlm_*.pth` 作为预训练的输出权重(其中*为模型的dimension,默认为512) > 执行预训练,得到 `pretrain_vlm_*.pth` 作为预训练的输出权重(其中*为模型的dimension,默认为512)
@ -242,7 +242,7 @@ python trainer/train_pretrain_vlm.py --epochs 4 --from_weight llm
```bash ```bash
# 基础训练命令(从预训练权重开始,全参数微调) # 基础训练命令(从预训练权重开始,全参数微调)
python trainer/train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm python train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm
``` ```
> 执行监督微调,得到 `sft_vlm_*.pth` 作为指令微调的输出权重 > 执行监督微调,得到 `sft_vlm_*.pth` 作为指令微调的输出权重
@ -258,7 +258,7 @@ python trainer/train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm
```bash ```bash
# 训练中断后,使用相同命令并添加 --from_resume 1 # 训练中断后,使用相同命令并添加 --from_resume 1
python trainer/train_sft_vlm.py --epochs 4 --from_resume 1 python train_sft_vlm.py --epochs 4 --from_resume 1
``` ```
**参数说明:** **参数说明:**

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@ -240,7 +240,7 @@ Please reserve about 5GB of space for the dataset. If there is insufficient spac
```bash ```bash
# Basic training command (start from LLM weights, train vision_proj only) # Basic training command (start from LLM weights, train vision_proj only)
python trainer/train_pretrain_vlm.py --epochs 4 --from_weight llm python train_pretrain_vlm.py --epochs 4 --from_weight llm
``` ```
> Run pretraining to get `pretrain_vlm_*.pth` as the pretrained model's output weights (* represents the model > Run pretraining to get `pretrain_vlm_*.pth` as the pretrained model's output weights (* represents the model
@ -250,7 +250,7 @@ python trainer/train_pretrain_vlm.py --epochs 4 --from_weight llm
```bash ```bash
# Basic training command (start from pretrain weights, full parameter fine-tuning) # Basic training command (start from pretrain weights, full parameter fine-tuning)
python trainer/train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm python train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm
``` ```
> Perform supervised fine-tuning to get `sft_vlm_*.pth` as the output weights for the fine-tuned model. > Perform supervised fine-tuning to get `sft_vlm_*.pth` as the output weights for the fine-tuned model.
@ -266,7 +266,7 @@ python trainer/train_sft_vlm.py --epochs 2 --from_weight pretrain_vlm
```bash ```bash
# To resume training after interruption, use the same command and add --from_resume 1 # To resume training after interruption, use the same command and add --from_resume 1
python trainer/train_sft_vlm.py --epochs 4 --from_resume 1 python train_sft_vlm.py --epochs 4 --from_resume 1
``` ```
**Parameter Description:** **Parameter Description:**