首先,确认openai/clip-vit-large-patch14模型是否确实需要一个特定的tokenizer,或者该模型是否已经在transformers库中内置了tokenizer处理。对于CLIP模型,通常它们不是标准的文本到文本或文本到图像的transformer模型,因此可能需要特殊的处理方式。 2. 检查tokenizer文件是否完整且未损坏 由于CLIP模型不直接对应一个标准的tokeni...
openai-clip-vit-large-patch14 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...
这个错误提示说明加载'openai/clip-vit-large-patch14'模型的分词器(tokenizer)出现了问题。可能的原因是无法访问分词器文件。您可以尝试使用以下代码下载分词器文件:stylusimport openaiopenai.api_key = "YOUR_API_KEY"model_name = "openai/clip-vit-large-patch14"tokenizer = openai.api.Completion.create(engine...
部署Stable Diffusion玩转AI绘画(GPU云服务器) 本实验通过在ECS上从零开始部署Stable Diffusion来进行AI绘画创作,开启AIGC盲盒。 关于openai/clip-vit-large-patch14的报错,要手动下载,并且要修改源文件路径。 源文件 vim repositories/stable-diffusion-stability-ai/ldm/modules/encoders/modules.py 找到其中的openai/c...
("openai/clip-vit-large-patch14", return_dict=False, torchscript=True) processor = CLIPProcessor.from_pretrained("openai/clip-vit-large-patch14") url = "http://images.cocodataset.org/val2017/000000039769.jpg" image = Image.open(requests.get(url, stream=True).raw) inputs = processor(text...
需要提前单独下载并保存于本地'''def__init__(self,version='/本地路径/clip-vit-large-patch14',...
绘世启动报错!..报错内容Can't load tokenizer for 'openai/clip-vit-large-patch14'. If you were trying to load it from '(有
Large vision transformer (ViT-L) 14 个patch(每个图像分为 14x14 像素patches/sub-images) 输入图像为336x336 pixel 对于文本编码器,CLIP 使用类似于 GPT-2 但更小的 Transformer 模型。他们的基础模型只有 63M 参数和 8 个注意力头。作者发现文本编码器的容量对 CLIP 的性能不太敏感。
I'm struggling with the sioze of the openai/clip-vit-large-patch14 model, thus I want to convert it to OPTIMUM onnx! Your contribution no ideas so far.. Hi@antje2233, which command are you running?optimum-cli export onnx --model openai/clip-vit-large-patch14 clip_onnx --task zero...
Can't load..这是什么问题?我试过了很多办法 开梯 改代码之类的 都无法解决 询问了Github的大佬 都不会 不知道为什么你们很多人都没事???