Entry Point AI - Fine-tuning Platform for Large Language Models VS Atlas对比,Entry Point AI - Fine-tuning Platform for Large Language Models 和 Atlas 有什么区别?
Entry Point is a no-code platform that helps you create custom AI models for your business or projects. Manage training data, generate synthetic examples, estimate fine-tuning costs, and optimize models — all in one place!
Entry Point AI - Fine-tuning Platform for Large Language Models 着陆页
With Atlas, you can easily generate highly detailed and diverse 3D models from reference images and text. A cutting-edge generative 3D AI technology to enable the creation of assets & virtual worlds in a fraction of the time it takes using traditional methods!
Atlas 着陆页
类别 | 大型语言模型(LLMs), AI项目管理, 无代码&低代码平台, AI 工作流程管理 |
Entry Point AI - Fine-tuning Platform for Large Language Models 网站 | https://www.entrypointai.com?utm_source=toolify |
添加时间 | 2023年6月8日 |
Entry Point AI - Fine-tuning Platform for Large Language Models 定价 | -- |
类别 | AI 3D模型生成器, 文本转3D工具, AI 内容生成器, AI 相片和图像生成器, 图像转图像工具, AI标志生成器, AI 设计生成器, 图像转3D模型工具, AI艺术生成器, AI插图生成器, AI背景生成器, AI横幅生成器, AI头像生成器, AI图形设计, AI封面生成器, 照片和图像编辑器, AI壁纸生成器, 设计助手, AI海报生成器 |
Atlas 网站 | https://atlas.design?utm_source=toolify |
添加时间 | 2024年3月20日 |
Atlas 定价 | -- |
To use Entry Point AI, follow these steps: 1. Identify the task you want your language model to perform. 2. Import examples of the desired task into Entry Point AI using a CSV file. 3. Evaluate the performance of the fine-tuned models using the built-in evaluation tools. 4. Collaborate with teammates to manage the training process and track model performance. 5. Utilize dataset tools to filter, edit, and manage your dataset. 6. Generate synthetic examples using the AI Data Synthesis feature. 7. Export the fine-tuned models or use them directly in your applications.
Using Atlas, you can generate 3D models by providing reference images and text. The AI technology will create highly detailed and diverse models in a fraction of the time.
Entry Point AI - Fine-tuning Platform for Large Language Models 是月访问量为 21.0K 且平均访问时长为 00:00:22 的工具。 Entry Point AI - Fine-tuning Platform for Large Language Models 的每次访问页数为 1.69,跳出率为 48.56%。
月访问量 | 21.0K |
平均·访问时长 | 00:00:22 |
每次访问页数 | 1.69 |
跳出率 | 48.56% |
Atlas 是月访问量为 1.4K 且平均访问时长为 00:01:28 的工具。 Atlas 的每次访问页数为 2.42,跳出率为 48.15%。
月访问量 | 1.4K |
平均·访问时长 | 00:01:28 |
每次访问页数 | 2.42 |
跳出率 | 48.15% |
Entry Point AI - Fine-tuning Platform for Large Language Models 的前 5 个国家/地区是:United States 30.03%, India 11.30%, Pakistan 10.05%, Germany 7.12%, Vietnam 5.12%
![]() | 30.03% |
11.30% | |
10.05% | |
7.12% | |
5.12% |
Atlas 的前 4 个国家/地区是:United States 52.91%, Brazil 22.38%, Italy 21.04%, United Kingdom 3.67%
![]() | 52.91% |
![]() | 22.38% |
21.04% | |
![]() | 3.67% |
Entry Point AI - Fine-tuning Platform for Large Language Models 的 6 个主要流量来源是:自然搜索 50.62%, 直接访问 36.69%, 外链引荐 7.40%, 社交媒体 4.49%, 展示广告 0.70%, 邮件 0.09%
自然搜索 | 50.62% |
直接访问 | 36.69% |
外链引荐 | 7.40% |
社交媒体 | 4.49% |
展示广告 | 0.70% |
邮件 | 0.09% |
Atlas 的 6 个主要流量来源是:自然搜索 52.52%, 直接访问 34.73%, 社交媒体 6.08%, 外链引荐 6.05%, 展示广告 0.53%, 邮件 0.08%
自然搜索 | 52.52% |
直接访问 | 34.73% |
社交媒体 | 6.08% |
外链引荐 | 6.05% |
展示广告 | 0.53% |
邮件 | 0.08% |
Entry Point AI - Fine-tuning Platform for Large Language Models 可能比 Atlas 更受欢迎。如您所见,Entry Point AI - Fine-tuning Platform for Large Language Models 每月有 21.0K 次访问,而 Atlas 每月有 1.4K 次访问。 所以更多的人选择了Entry Point AI - Fine-tuning Platform for Large Language Models。 因此,人们很可能会在社交平台上更多地推荐 Entry Point AI - Fine-tuning Platform for Large Language Models。
Entry Point AI - Fine-tuning Platform for Large Language Models 的平均访问持续时间为 00:00:22,而 Atlas 的平均访问持续时间为 00:01:28。 此外,Entry Point AI - Fine-tuning Platform for Large Language Models 的每次访问页面为 1.69,跳出率为 48.56%。 Atlas 的每次访问页面为 2.42,跳出率为 48.15%。
Entry Point AI - Fine-tuning Platform for Large Language Models 的主要用户是United States, India, Pakistan, Germany, Vietnam,分布如下:30.03%, 11.30%, 10.05%, 7.12%, 5.12%。
Atlas 的主要用户是 United States, Brazil, Italy, United Kingdom,分布如下:52.91%, 22.38%, 21.04%, 3.67%。