def example_CLIPVisionModel(): from PIL import Image import requests from transformers import AutoProcessor, CLIPVisionModel model = CLIPVisionModel.from_pretrained("openai/clip-vit-base-patch32") processor = AutoProcessor.from_pretrained("openai/clip-vit-base-patch32") url = "http://images.coco...
Describe the bug ImportError: cannot import name 'CLIPVisionModelWithProjection' from 'transformers' (/usr/local/lib/python3.9/dist-packages/transformers/init.py) 1 hour ago it worked nice. Reproduction No response Logs No response Syste...
python-3.x 属性错误：“CLIPVisionModelWithProjection”对象没有属性“get_image_features”我正在研究一...
通过将文本信息和图像信息进行融合,cliptextmodelwithprojection能够更好地理解输入数据,从而在各种应用场景中取得更好的表现。 这种模型可以应用于许多领域,例如新闻分类、情感分析、问答系统等。通过将文本和图像信息结合起来,cliptextmodelwithprojection可以更好地理解上下文信息,从而更准确地分类或生成文本。 此外,clip...
if comfy.model_management.should_use_fp16(self.load_device, prioritize_performance=False): self.dtype = torch.float16 with comfy.ops.use_comfy_ops(offload_device, self.dtype): with modeling_utils.no_init_weights(): self.model = CLIPVisionModelWithProjection(config) self.model.to(self.dtype)...
cliptextmodelwithprojection ClipTextModel with projection(投影剪辑文本模型)是一种使用投影方法对文本进行剪辑的模型。该模型旨在将输入文本剪辑为与训练过的图像特征相似的向量表示。 剪辑文本模型的基本思想是利用预训练的图像剪辑模型,例如Clip中的图像特征,来对文本进行剪辑。通过将文本和图像特征进行投影,将文本从...
(module, CLIPVisionModelWithProjection): nn.init.normal_( module.visual_projection.weight, std=self.config.hidden_size**-0.5 * self.config.initializer_factor, ) elif isinstance(module, CLIPTextModelWithProjection): nn.init.normal_( module.text_projection.weight, std=self.config.hidden_size**-...
First, let’s create a model.js file. Importing required libraries These libraries handle image preprocessing, tokenization, model inference, and PostgreSQL vector operations. #Model.js import { AutoProcessor, AutoTokenizer, CLIPVisionModelWithProjection, CLIPTextModelWithProjection, RawImage } from '@...
classCLIP(nn.Module):def__init__(self,embed_dim:int,#512# vision image_resolution:int,#224vision_layers:Union[Tuple[int,int,int,int],int],#12vision_width:int,#768vision_patch_size:int,#32# text context_length:int,#77vocab_size:int,#49408transformer_width:int,#512transformer_heads:int...
import { AutoTokenizer, CLIPTextModelWithProjection, AutoProcessor, CLIPVisionModelWithProjection, RawImage, cos_sim } from '@xenova/transformers'; // Load tokenizer and text model const tokenizer = await AutoTokenizer.from_pretrained('jinaai/jina-clip-v1'); const text_model = await CLIPText...