Hugging Face Reviews

Neeraj V.Junior Software Developer

5.0

Ultimately, it wouldn't be an exaggeration to say the growth of AI and AI products wouldn't have happened this fast without Huggingface. Even their logo and website design has a refreshing effect on the mind Review collected by and hosted on G2.com.

Varun Ganjigunte P.Small-Business(50 or fewer emp.)

5.0

Moreover, our research projects can be easily deployed as a demo interface (using gradio) for quick public review. The quality of documentation and support provided by HF is exceptional. Review collected by and hosted on G2.com.

Shubham R.Data Scientist - (Advance Data Analyst)

5.0

Hugging Face is a platform for AI engineers that helps us to build, train deploy AI ML models. it gives pre-trained models that are pre-trained on very large data. We just need to use that infrastructure and train and deploy our own model. they have a Model Repository for Computer vision, NLP, and AI tasks. It is open- A source tool for any business with basic AI knowledge and uses the pre-trained model from hugging face and deploying model for their business. It has an AI community where you can share and view AI research best platform for Research and deployment. It saves much of AI engineer time cost cost-effective and needs less GPU to train as we can use pre-trained API. Review collected by and hosted on G2.com.

Verified User in ResearchMid-Market(51-1000 emp.)

4.0

Only concern I found was resource -intensive in terms of memory and computation. Review collected by and hosted on G2.com.

Tom W.Filmmaker

4.0

It can be a little challenging to navigate, but once you figure it out, the platform is very usable. Review collected by and hosted on G2.com.

Pranshu G.Software Developer

4.0

Some of the models and spaces do not have reliable infrastructure support. The server crashes quite often. Review collected by and hosted on G2.com.

Verified UserEmployee

10.0

We use Hugging Face APIs to import the models in our code (mostly language models with weights). This is very important use case as it makes the building part of model very easy. We don't have to spend much time refering to repositories, reading complex ReadMe's. Other than that, we deploy demo apps on the Hugging Face spaces using the gradio tool they provide. This helps in testing out the product very easily by not spending much time on making the UI and also not caring about the compute management.

Verified UserTeam Lead

10.0

We use Hugging Face models and datasets to design, test a compare multiple approaches for ML projects and, and in general, for research purposes. Thanks to Hugging Face, we do not need extensive training, and our NLP models' fine-tuning is simpler and more cost efficient.
NLP models NLP datasets Version control for models and datasets.

Vijay IrlapatiAssociate Lead Engineer

10.0

For most of the ML problems, we use hugging face prediction models as these models give better performance than any other models. It helps in addressing the technological advancements in an organisation. Any organisation that wants to adopt to latest technologies should consider Hugging face. Hugging face has many open-source transformer models hosted. The scope of this product is to give better performance on NLP problems.
Has access to hundreds of models useful for any NLP usecase. Gives better accuracy on prediction tasks. Easy to test the model in the website itself to check the accuracy without actually implementing it. Has many algorithms for all the prediction problems.

Verified UserTeam Lead

8.0

Hugging Face keeps handy when you work with machine learning projects specially neuronal networks. Neuronal networks are complex and becomes cumbersome when you perform transformation on it. We are resolving this issue with Hugging Face. It has huge amount of libraries with pre-trained models which are optimised too. Hugging Face plays a vital role in machine learning models.
Libraries documentations can be improved. sometime hard to select appropriate libraries. Can add more features.

Verified UserAnalyst

9.0

In our organization, Hugging Face is used for a lot of text-processing and natural language processing tasks. Hugging face addresses our business problem of finding good NLP algorithms for running classification analysis by using open source API to keep our costs low. The website provides world's best systems for doing NLP and using this model, we are able to do advance NLP analyses and classification using text data.

Ivan CuiData Scientist II

9.0

I have use Hugging Face to develop Natural Language Processing applications for other amazon web services customers. Some of the common applications are intelligent document processing, call center support, machine translation, sentiment analysis and so on. These Hugging Face solutions are implemented on the cloud for easier manage and maintain as well.
Better documentation Have dedicated support