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Hugging Face Spaces 是什么？ Hugging Face Spaces 是 Hugging Face Hub 上提供的一项服务，它提供了一个易于使用的 GUI，用于构建和部署 Web 托管的 ML 演示及应用。 该服务使得用户可以快速构建 ML 演示、上传要托管的自有应用，甚至即时部署多个预配置的 ML 应用。 From the documentation for from_pretrained, i understand i don't have to download the pretrained vectors every time, i can save them and load from disk with this syntax 对于国内用户，最方便的方式是使用迅雷下载，但是中间还是可以有一些小技巧的。 下面以下载deepseek-R1-0528，671b版本为例，160多个参数文件，hugging face没有给出一键下载全部内容的链接，而手动一个一个地下载又太蠢了，但是实践发现不同序号的权重的下载地址就是个数字不一样而已，因此我们.
说句题外话，百度的那个 paddleNLP 是真的难绷，本来就没啥模型，社区还要找半天，我从百度 aistudio 上面传一个 llama7B 的参数还要开一个迅雷会员+一个百度会员，无语。。。 aistudio虽然有免费的GPU，但禁止 pytorch，他们写的参数convert脚本有import torch， 因此也一个都用不了。 再看看抱脸，已经成为LLM. To gain full voting privileges, Hugging Face 发布机器人课程 我们的课程更新啦🔥 这次是免费机器人课程《Robotics Course》 课程将从零开始，讲解如何让机器人真正“理解”和“行动”。 机器人新手，开发者，研究员都适合！ 课程亮点： 🔴 经典机器人学基础：掌握感知、控制与运动规划的核心原理 🔴 强化学习在真实机器人中的…
I'm relatively new to python and facing some performance issues while using hugging face transformers for sentiment analysis on a relatively large dataset
I've created a dataframe with 6000 rows o. Loading hugging face model is taking too much memory asked 2 years, 7 months ago modified 2 years, 6 months ago viewed 16k times 20231019亲测清华源失效，其它各种站点要么模型不全，要么下载太慢。 后来发现hugging face的仓库是基于git进行远程管理的。 所以理论上可以
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