ControlUp vs. Hugging Face

An environment where visibility of general performance metrics isn't currently done or is done with a system that is difficult to use (which was our case). An environment where resource allocation decisions need to be made (e.g. how much RAM and CPU to allocate to VM pools). An environment where a troubleshooting tool is needed (e.g. to answer the question, "Why is this person experiencing poor performance right now?")

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

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• The triggers are very flexible and can be configured to alert on things from events in sessions to hardware failures. Script actions are what they sound like. They are scripts that can be created and run on demand or tied to a trigger. One example is that if a hard drive is low on space we have a script to clean up certain things on the drive.
• Script actions are supported by the ControlUp community. Community members can submit scripts that are reviewed by ControlUp and approved. This means more script are added over time.
• ControlUp support and sales support has been great. Our sales engineer is always willing to jump on and help us with configuration issues and standard support is quick to respond and are good at resolving issues.

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

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• It seems that there is a gradual transition occurring from one interface (a local program) to another (Web). This creates confusion at times.
• ScoutBees module has a problem with our version of Horizon, so we can't do a login test
• The local program for ControlUp uses a lot of resources
• The training session focus on very large environments, which we aren't. Might be good to offer SMB sessions separately.

• 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.

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I feel all these products are good and have their strengths but for me it came down to two categories. How easy is it to find issues and cost. It seemed to me that the easiest to use is ControlUp and eG. Price broke down to ControlUp and SysTrack being lower than Goliath and eG.

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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.

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• its licensing cost is a bit on high

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

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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