Amazing open source project that gives best access than any other product
Rating: 10 out of 10
IncentivizedUse Cases and Deployment Scope
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.
Pros
- 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.
Cons
- Most of the Hugging face models are of big size, hence difficult to work if there is no access to high computational system like GPU.
- It’s good to have some visualization tool in hugging face for viewing model architecture.
- I recommend to implement hugging face lite version so that it can run on any system with less specifications.
Likelihood to Recommend
If an organisation has more access to data and have access to high end computers like GPUs it’s recommended to use Hugging face as it will give better accuracy than any other models. If an organisation having less data and has less access to GPUsis looking for decent performance then traditional algorithms are more appropriate than hugging face