Hugging Face vs. StackState

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

Incentivized

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StackState is suitable for 1000+ hosts. Sometimes specific applications can take higher development time. Well suited for hybrid platforms to build end to end service alarms and service views. Advanced UI navigation might require some training. It is not a simple download and deploy software. It will require development in an agile model. Where newer versions are deployed to suit exact client requirements. Support contract with the StackState Engineer for development of use-cases is required and very useful.

• Model APIs
• Hugging Face Spaces for deploying demo apps
• Latest updated models available easily
• Vast support for language parsing and other relevant tasks

Incentivized

Independently Invited by TrustRadius

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• Giving observability of the entire IT stack
• Custom alerting options.
• Ingesting many different types of data.
• Requesting new features is encouraged and they often add them quite quickly.

• 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.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Can't think of anything yet.

Some elements of the product haven't had the usability upgrade yet and can be a bit technical. This is to be expected as they are trying to solve complex problems. I am sure that in the future, steps will be made to simplify this as well for the users / administrators / developers of the platform.

It's swift, they're thinking along with us. It's a "collaboration approach" rather than a (traditional) customer-supplier relation. Out new ideas are taken in concern and often ends up in enhancements of StackState

There are some other services offer similar capacity as to Hugging Face, but not entirely the same. For example, amazon web services have a machine learning service called Comprehend, which offer a set of easy to use APIs to do machine translation and entity recognition and some other common NLP use case.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Hugging Face is cost and time saving.
• Pay is less, you pay what you use, doesn't affect much.
• Overall positive impact on business.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Increased visibility of all resources in cloud to 100%.
• Deviated stages are able to detect problems before their occurrence. However, [it] needs tunings for false alarms.