Python/AI Engineer at Wokegenics Solutions Private Limited
Real User
Top 20
2024-09-04T14:56:10Z
Sep 4, 2024
To use Hugging Face, you need to have basic knowledge of how to feed the data, how to speed data, how to train the model, and how to evaluate the model. Compared to other frameworks like PyTorch and TensorFlow, I'm more comfortable with using Hugging Face. I would recommend the solution to other users. Overall, I rate the solution seven and a half out of ten.
You can start with it on a personal device. If you're planning to deploy, you might want to consider integrating Hugging Face with a cloud platform. This can help reduce charges, and the deployment will happen on the cloud platform. If you're joining our team and using this tool for the first time, you'll need some experience deploying models. Hugging Face is one platform where you can deploy open-source models. You should have six or seven months of experience handling large language models. After that, you can learn the basic documentation in two or three days. I rate it an eight out of ten.
Hugging Face is suitable if you are serious about your product and want to keep your data private instead of using peer services. It's good for learning and exploring AI models.
Lead RND Engineer, Data Scientist at a healthcare company with 11-50 employees
Real User
Top 20
2023-09-04T10:02:00Z
Sep 4, 2023
Hugging Face is the main hub for large language models and AIs. I would recommend it to anyone who's considering using it. Overall, I rate it a nine out of ten.
AI Development Platforms are software frameworks that provide developers with tools and resources to build, train, and deploy AI models and applications.
To use Hugging Face, you need to have basic knowledge of how to feed the data, how to speed data, how to train the model, and how to evaluate the model. Compared to other frameworks like PyTorch and TensorFlow, I'm more comfortable with using Hugging Face. I would recommend the solution to other users. Overall, I rate the solution seven and a half out of ten.
You can start with it on a personal device. If you're planning to deploy, you might want to consider integrating Hugging Face with a cloud platform. This can help reduce charges, and the deployment will happen on the cloud platform. If you're joining our team and using this tool for the first time, you'll need some experience deploying models. Hugging Face is one platform where you can deploy open-source models. You should have six or seven months of experience handling large language models. After that, you can learn the basic documentation in two or three days. I rate it an eight out of ten.
Hugging Face is suitable if you are serious about your product and want to keep your data private instead of using peer services. It's good for learning and exploring AI models.
Overall, I would rate it nine out of ten.
Hugging Face is the main hub for large language models and AIs. I would recommend it to anyone who's considering using it. Overall, I rate it a nine out of ten.