Comments (1)
您好,关于图像描述任务,欢迎参见我们团队的最新工作Qwen-VL哈~ 欢迎关注通义千问系列模型
https://github.com/QwenLM/Qwen-VL
from chinese-clip.
Related Issues (20)
- Text-to-Image Retrieval & Image-to-Text Retrieval速度太慢,怎么进行合理加速
- 基于模型微调后得到epoch_latest.pt,但是为什么训练完推理不了,我试了好几个服务器跑完都不行 HOT 2
- 训练时存在内存泄露的问题。 HOT 1
- inference速度慢
- 请问CLIPTokenizer和Chinese-CLIP中的什么对应呢? HOT 5
- 中文和英文同时匹配图片时中文得分非常低
- 无法识别图片里面的中文 HOT 2
- 使用默认超参数在COCO-CN上微调,无法收敛
- 源码中的一些bug,请确认下~
- train.py中sampler.set_epoch的判断不够严谨
- 相似度计算实测下来完全不对 HOT 3
- 转换onnx失败 HOT 2
- 为什么使用gpu进行推理比cpu还慢? HOT 1
- AttributeError: 'NoneType' object has no attribute 'get' HOT 5
- 这个支持词性标注吗 HOT 1
- ImportError: cannot import name 'convert_state_dict' from 'cn_clip.clip.model' HOT 2
- AttributeError: 'Namespace' object has no attribute 'use_flash_attention' HOT 2
- load_from_name function logic problem
- torch onnx tensorrt 推理速度和deployment.md评估效果差异较大 HOT 1
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