We performed a comparison between Hugging Face and TensorFlow based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."
"My preferred aspects are natural language processing and question-answering."
"Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers."
"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."
"TensorFlow is a framework that makes it really easy to use for deep learning."
"It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment."
"It's got quite a big community, which is useful."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"The area that needs improvement would be the organization of the materials. It could be clearer and more systematic. It would be good if the layout was clear and we could search the models easily."
"Implementing a cloud system to showcase historical data would be beneficial."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models."
"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."
"The solution is hard to integrate with the GPUs."
"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."
"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications."
"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."
Hugging Face is ranked 8th in AI Development Platforms with 3 reviews while TensorFlow is ranked 4th in AI Development Platforms with 16 reviews. Hugging Face is rated 9.0, while TensorFlow is rated 9.0. The top reviewer of Hugging Face writes "A comprehensive natural language processing ecosystem offering a diverse range of pre-trained models and a collaborative platform". On the other hand, the top reviewer of TensorFlow writes "Effective deep learning, free to use, and highly stable". Hugging Face is most compared with Google Vertex AI, Azure OpenAI, Replicate, Google Cloud AI Platform and Amazon SageMaker, whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, OpenVINO, IBM Watson Machine Learning and Azure OpenAI. See our Hugging Face vs. TensorFlow report.
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