Transformers Autoimageprocessor. from transformers import AutoImageProcessor processor = AutoI
from transformers import AutoImageProcessor processor = AutoImageProcessor. dev1178+g4346db5fa transformers 5. Jan 5, 2025 · kun432さんのスクラップ 事前学習済みトークナイザをロードする。これにより、入力するテキストは、事前学習モデルが使用した学習データと同じルールで分割され、そして事前学習モデルと同じボキャブ（トークンと数値インデックスのマッピング）で、処理されることになる。 >>> from transformers import AutoImageProcessor >>> import torch >>> image_processor = AutoImageProcessor. An extended family of versatile vision foundation models producing high-quality dense features and achieving outstanding performance on various vision tasks This wrapper integrates the state-of-the-art Depth Anything 3 model for monocular depth estimation. from_pretrained(checkpoint) from transformers import AutoImageProcessor processor = AutoImageProcessor. intermediate_size (int, optional, defaults to 3072) — Dimensionality of the “intermediate” (i. Aug 13, 2025 · We’re on a journey to advance and democratize artificial intelligence through open source and open science. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and Jul 11, 2024 · Learn how to train RT-DETR on a custom dataset using the Transformers library. 🤗 Transformers 提供了一组预处理类来帮助准备数据以供模型使用。 在本教程中，您将了解以下内容： 对于文本，使用 分词器 (Tokenizer)将文本转换为一系列标记 (tokens)，并创建 tokens 的数字表示，将它们组合成张量。 Image classification Image segmentation Video classification Object detection Zero-shot object detection Zero-shot image classification Depth estimation Image-to-Image Image Feature Extraction Mask Generation Keypoint detection Knowledge Distillation for Computer Vision Keypoint matching Dec 12, 2023 · from transformers import Dinov2Config, Dinov2ForImageClassification, AutoImageProcessor image_height, image_width = 1080, 1920 checkpoint = "facebook/dinov2-base" # Create a new model with randomly initialized weights model_config = Dinov2Config. Likewise, if your NewModel is a subclass of PreTrainedModel, make sure its config_class attribute is set to the same class you use when registering the model (here NewModelConfig).