open_clip.create_model_and_transforms( model_name="coca_ViT-L-14", pretrained="mscoco_finetuned_laion2B-s13B-b90k", cache_dir=r'本地地址' ) 然后在本地地址找到模型,传到服务器的~/.cache/huggingface/hub路径下 然后在服务器端运行 model, _, transform = open_clip.create_model_and_transfo...
importopen_clipimporttorchfromPILimportImagemodel,_,transform=open_clip.create_model_and_transforms(model_name="coca_ViT-L-14",pretrained="mscoco_finetuned_laion2B-s13B-b90k")im=Image.open("cat.jpg").convert("RGB")im=transform(im).unsqueeze(0)withtorch.no_grad(),torch.cuda.amp.autocas...
This repository is focused on training CLIP models. To fine-tune atrainedzero-shot model on a downstream classification task such as ImageNet, please seeour other repository: WiSE-FT. TheWiSE-FT repositorycontains code for our paper onRobust Fine-tuning of Zero-shot Models, in which we introd...
clip-fine-tuning.ipynb updated notebook for training Oct 20, 2022 download_data.sh updated app Nov 1, 2022 embeddings.npy updated embeddings and inference notebook Oct 20, 2022 fine_tune_clip.py updated notebook for training Oct 20, 2022 inference.ipynb updated embeddings and inference notebook...
干货预警:这可能是你能够找到的最容易懂的,最完整的,适用于各种NLP任务的开源LLM的finetune教程~ lyhue1991 2023/09/05 7790 AIGC之文本和图片生成向量 aigc 文本和图片生成向量的方式一般是通过已有的模型进行生成,在流行的模型托管平台上已有大量开源的Embedding模型,如国外的HuggingFace平台和国内的ModelScope平台。
One can also use the non -quickgelu model definitions with pretrained weights using QuickGELU but there will be an accuracy drop, for fine-tune that will likely vanish for longer runs.Future trained models will use nn.GELU.>>> import open_clip >>> open_clip.list_pretrained() [('RN50'...
Qwen-VL基于Lite Server适配PyTorch NPU的Finetune训练指导(6.3.912) aarch64 配置IP转发,用于容器内的网络访问。执行以下命令查看net.ipv4.ip_forward配置项的值,如果为1,可跳过此步骤。 sysctl -p | grep net.ipv4.ip_forward 如果net.ipv4.ip_forward配置项的值不为1,执行以下命令配置IP转发。
对于Image Encoder,CLIP使用“ViT-L/14@336px”这个模型,也就是架构为Large,patch_size = 14的ViT,同时在整个CLIP预训练结束后,用更高分辨率(336*336)的图片做了一个epoch的fine-tune,目的是让CLIP能涌现出更好的效果。与Text Encoder类似,每张图片对应一个最终特征表示向量Ii。
coca_ViT-L-14,mscoco_finetuned_laion2b_s13b_b90k,638.45,214.52,0.6159,0.7204,0.9420,0.9630,0.7965,0.3765,0.2501,0.1800,0.6213,0.5867,0.2329,0.8436,0.5453,0.6114,0.6475,0.4548,0.3865,0.8574,0.3797,0.8292,0.6253,0.7074,0.9115,0.8106,0.4943,0.6107,0.6267,0.8865,0.9861,0.7398,0.5564,0.8373,0.6028,0.514...
Specifically, we construct a region image dataset with different IoU and adopt IoU values as labels to fine-tune the CLIP model to learn IoU-aware and class-agnostic semantic prompts and visual embeddings. The fine-tuned IoU-CLIP can predict IoU scores for proposals, which interact with ...