openai-clip-vit-base-patch32 Overview OpenAI's CLIP (Contrastive Language–Image Pre-training) model was designed to investigate the factors that contribute to the robustness of computer vision tasks. It can seamlessly adapt to a range of image classification tasks without requiring specific training...
display_labels=labels)disp.plot(xticks_rotation="vertical")在clip-vit-base-patch32模型上的accuracy...
以clip-vit-base-patch32为例: CLIPModel( (text_model): CLIPTextTransformer( (embeddings): CLIPTextEmbeddings( (token_embedding): Embedding(49408, 512) (position_embedding): Embedding(77, 512) ) (encoder): CLIPEncoder() ) (vision_model): CLIPVisionTransformer( (embeddings): CLIPVisionEmbeddings...
from transformers import CLIPTokenizerFast, CLIPProcessor, CLIPModel 接下来,我们加载 CLIP 模型的权重、分词器和图像处理器: device = "cuda" if torch.cuda.is_available() else "cpu" model_id = "openai/clip-vit-base-patch32" # we initialize a tokenizer, image processor, and the model itself t...
type='HuggingCLIPLanguageBackbone', model_name='pretrained_models/clip-vit-base-patch32-projection', model_name='openai/clip-vit-base-patch32', frozen_modules=['all'])), neck=dict(type='YOLOWolrdDualPAFPN', guide_channels=text_channels, ...
你可以在自己的计算机上使用HuggingFace的Transformers库用几行代码就使用CLIP!首先,导入库并加载预训练模型。 importtransformers model = transformers.CLIPModel.from_pretrained("openai/clip-vit-base-patch32") processor = transformers.CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32") ...
Some weights of the model checkpoint at openai/clip-vit-base-patch32 were not used when initializing CLIPTextModelWithProjection: ['vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.1.self_attn.out_proj.weight', 'vision_model.encoder.layers.2.mlp.fc1.bias', '...
根据OpenAI 披露的技术报告,Sora 的核心技术点之一是将视觉数据转化为 patch 的统一表征形式,并通过 Transformer 和扩散模型结合,展现了卓越的扩展(scale)特性。在报告公布后,Sora 核心研发成员 William Peebles 和纽约大学计算机科学助理教授谢赛宁合著的论文《Scalable Diffusion Models with Transformers》就成了众多研究...
(version) File "D:\AIAI\stable-diffusion-webui_23-01-20\python\lib\site-packages\transformers\tokenization_utils_base.py", line 1785, in from_pretrained raise EnvironmentError(OSError: Can't load tokenizer for 'openai/clip-vit-large-patch14'. If you were trying to load it from 'https:/...
LLM 的成功一定程度上取决于其统一的不同模态的表征,比如代码、数学、各种语言都可以使用 Token 表示。在 Sora 中作者也借鉴了这个思路,使用 ViT 等模型采用的图像 Patch 作为高度可扩展且有效的表征,用于在不同类型的视频和图像上训练生成模型。 具体来说,首先使用 Visual Encoder 将视频压缩为隐空间(Latent Space...