Comments (1)
比性能的话,不是一个level的,Qwen-VL性能很好,第二个stage是全参数训练,数据量也比较大。如果用更大的语言模型 + 更多的数据可能还能稍微拼拼吧,具体还没有尝试
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Related Issues (20)
- Error:safetensors_rust.SafetensorError: Error while deserializing header: HeaderTooLarge HOT 1
- 请问如何用Qwen-14B进行重新训练 HOT 3
- deepspeed training, meet the error "ValueError: optimizer got an empty parameter list" HOT 4
- 请问如何减少训练时长 HOT 2
- 请问是否支持 流水线并行 推理 HOT 2
- 请问Qwen-7B的权重文件是只需要LFS的吗?还是全部文件都要呢? HOT 2
- 关于知乎中提到的多模态接入方案问题 HOT 6
- 是否支持QWEN-14B的INT4的量化版本? HOT 3
- 分布式设置错误 HOT 1
- Probably lower loss when use `train_pipeline.py` HOT 1
- video-chat example upload
- AI 无法理解图片 HOT 10
- DeepSpeed的PP需要相同的seq-length(collate时注意padding)和batchsize(将dataloader的`drop_last`设为True) HOT 11
- 请教一下关于SFT的问题 HOT 3
- 学习率一直是1e-4不会下降? HOT 3
- 训练loss异常 HOT 6
- special token HOT 5
- 请教下为什么选用 qwen LLM 有和其他 baichuan2,chatglm3 做过比较么 HOT 3
- huggingface 下载的Qwen7B-chat/None HOT 1
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