可以使用以下代码从open_clip库中导入create_model_from_pretrained和get_tokenizer函数: python from open_clip import create_model_from_pretrained, get_tokenizer 这段代码假设你已经安装了open_clip库。如果尚未安装,可以通过以下命令进行安装: bash pip install open_clip 安装完成后,你就可以使用上述导入语句来...
CLIP 和 OpenCLIP 模型加载方式存在显著差异: 1. 加载 OpenAI 提供的 CLIP 使用Hugging Face提供的transformers库: pythonfrom transformers import CLIPModel, CLIPProcessor from PIL import Image # 加载模型 model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32") processor = CLIPProcessor.from_pr...
import torchfrom PIL import Imageimport open_clipmodel, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pretrained='laion2b_s34b_b79k')model.eval() # 模型默认处于训练模式，这会影响某些使用BatchNorm或随机深度的模型tokenizer = open_clip.get_tokenizer('ViT-B-32')image ...
These weights use a different dataset mean and std than others. Instead of using the OpenAI mean & std, inception style normalization[-1, 1]is used via a mean and std of[0.5, 0.5, 0.5]. This is handled automatically if usingopen_clip.create_model_and_transformsfrom pretrained weights. ...
else "cpu") clip_model_name = "ViT-L-14" clip_model,_,clip_preprocess = open_clip.create_model_and_transforms(clip_model_name clip_model_name,pretrained = "openai",precision='fp16' if device == 'cuda' else 'fp32',device=device, ) tokenize = open_clip.get_tokenizer(clip_model_name...
Image Credit:https://github.com/openai/CLIP Usage pip install open_clip_torch importtorchfromPILimportImageimportopen_clip model, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32-quickgelu', pretrained='laion400m_e32')
import os import torch from PIL import Image import open_clip if 'DEVICE_ID' in os.environ: print("DEVICE_ID:", os.environ['DEVICE_ID']) else: os.environ['DEVICE_ID'] = "0" model, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pretrained='/home/ma-user/ope...
importopen_clipimporttorch# 设置模型,可根据需要选择模型model,_,preprocess=open_clip.create_model_and_transforms('ViT-B-32',pretrained='laion2b_s34b_b79k')# 使用 torch 加载图像。这是一个占位符,具体实现取决于你的数据集。fromtorchvisionimportdatasets ...
'model': {'type': 'STDiT2-XL/2', 'from_pretrained': 'hpcai-tech/OpenSora-STDiT-v2-stage3', 'input_sq_size': 512, 'qk_norm': True, 'enable_flash_attn': True, 'enable_layernorm_kernel': True}, 'vae': {'type': 'VideoAutoencoderKL', 'from_pretrained': './opensora/models...
pip install open_clip_torch importtorchfromPILimportImageimportopen_clipmodel,_,preprocess=open_clip.create_model_and_transforms('ViT-B-32',pretrained='laion2b_s34b_b79k')model.eval()# model in train mode by default, impacts some models with BatchNorm or stochastic depth activetokenizer=open...