2.3 可控的生成模型 为了更好地约束生成图像的主题,有学者提出mask的方案,以及Pivot Tuning方案,然而这些方案都有着各自的限制,并不能满足我们的需求。以及同期的一篇工作:An image is worth one word: Personalizing text-to- image generation using textual inversion,该方法提出了一种通过在冻结的文本到图像模型的...
Fine tuning a text generation model using the GPT-2 architecture and a csv dataset - arham-kk/gpt2-finetune
DreamBooth 不仅做到了 subject-driven generation,即根据给定的几张图片,定制化地生成目标概念,而且还能够在生成目标概念的新图时,使得生成背景、风格等丰富多样。 先来看一下结果,可以看到,DreamBooth 将目标 subject 小狗生成了出来,保真度很高。而且,背景也很丰富多样,根据不同的 prompt,将小狗生成到了不同的场景中...
Ruiz N., Li Y., Jampani V., Pritch Y., Rubinstein M. and Aberman K. DreamBooth: Fine tuning text-to-image diffusion models for subject-driven generation. arXiv preprint arXiv:2208.12242, 2022. 概 可控文生图. Motivation 之前的文生图模型缺乏可控性. 虽然我们可以通过特别的模型生成大差不差...
Fine-Tuning Text-to-Image Generation Models Using Curriculum Learning for Yao Costume Image Generation 来自 IEEEXplore 喜欢 0 阅读量: 17 作者:Z Shi,B Xiong 摘要: With the emergence of diffusion models, synthesizing images from textual descriptions has become an active research field. However, ...
Why will you need fine-tuning an LLM? LLMs are generally trained on public data with no specific focus. Fine-tuning is a crucial step that adapts a pre-trained LLM model to a specific task, enhancing the LLM responses significantly. Although text generation is a well-known application of ...
decoded_text = tokenizer.decode(encoded_text) print("Decoded tokens back into text: ", decoded_text) 1. 2. 输出如下: Decoded tokens back into text: Hi, how are you? 1. 可以看到数据又被还原了。在尝试对多个数据进行编码解码。 list_texts = ["Hi, how are you?", "I'm good", "Yes"...
Fine-tuning in machine learning is the process of adapting a pre-trained model for specific tasks or use cases through further training on a smaller dataset.
Fine-tuning a masked language model.根据一定规则确定mask位置。mask 两个(多个)。只记录改动。封面:村重结月。
Lines 2–3: This is where we import the pretrained BART Large model that we will be fine-tuning. Lines 7–15: This is where everything is handled to create a mini-batch of input and targets. We also specify what is the task, along with a bunch of hyperparameters (in the text_gen...