Synthyra
Profluent - E1 是对 Profluent Bio 公司 E1 模型的忠实实现，由 Synthyra 发布。它是一个专注于蛋白质序列处理的预训练语言模型，集成了 Hugging Face AutoModel 兼容性，并提供高效的嵌入功能，旨在简化生物信息学任务中的蛋白质序列分析和表示学习。
Profluent-E1 是对 Profluent 官方 E1 模型的忠实实现，集成了 Hugging Face AutoModel 兼容性，专注于蛋白质序列的表示学习。它能够生成高质量的蛋白质序列嵌入，支持掩码语言建模、序列分类和标记分类等任务，并提供了便捷的嵌入提取和微调功能。
amaye15
AIMv2-Large-Patch14-Native 是一个适配后的图像分类模型，基于原始AIMv2模型修改，兼容Hugging Face Transformers的AutoModelForImageClassification类。
ltg
这是deberta-v2-xxlarge的更新版本，实现了AutoModelForCausalLM类，使其能够生成文本。修复了原始实现中的三个问题，包括输出嵌入权重名称、增强掩码解码器实现和位置嵌入截断处理。
Transformers%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)