从ViTPreTrainedModel继承的from_pretrained方法将ViTConfig对象传递给ViTForRegression类（代码）的__init__...
从ViTPreTrainedModel继承的from_pretrained方法将ViTConfig对象传递给ViTForRegression类（代码）的__init__...
self.config = config assert config.hidden_dim % config.num_heads == 0 # 判断是否可以整数划分为多头注意力 self.wq = nn.Linear(config.hidden_dim, config.hidden_dim, bias=False) self.wk = nn.Linear(config.hidden_dim, config.hidden_dim, bias=False) self.wv = nn.Linear(config.hidden_dim...
from transformers import SiglipConfig, SiglipVisionConfig from transformers.models.siglip.modeling_siglip import SiglipAttention from vllm_flash_attn import flash_attn_func from xformers.ops import memory_efficient_attentionfrom vllm.config import ModelConfig ...
System Info I am trying to import Segment Anything Model (SAM) using transformers pipeline. But this gives the following error : " RuntimeError: Failed to import transformers.pipelines because of the following error (look up to see its t...
从ViTPreTrainedModel继承的from_pretrained方法将ViTConfig对象传递给ViTForRegression类（代码）的__init__...
vision_transformers.ipynb Created using Colaboratory Jul 19, 2023 vit.py Add all axes explicitly May 8, 2023 README MIT license Vision Transformer from Scratch This is a simplified PyTorch implementation of the paperAn Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. The ...
from transformers import AutoTokenizer, AutoModelForCausalLM hf_path = 'tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B' model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True) model.cuda() config = model.config tokenizer = AutoTokenizer.from_pretrained(hf_path, use_fast=False,...
import timm model = timm.create_model( "vit_so400m_patch14_siglip_384.webli", pretrained=False, num_classes=0, dynamic_img_size=True, dynamic_img_pad=True, ) Contributor Author ChristopherCho commented Aug 1, 2024 @jeejeelee Hi, I believe that the pre-trained Siglip model vit_so400...
fromtorch.utils.dataimportDataLoaderfromtransformersimportCLIPProcessorfromdatachainimportC,DataChainprocessor=CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")chain=(DataChain.from_storage("gs://datachain-demo/dogs-and-cats/",type="image") .map(label=lambdaname:name.split(".")[0],para...