Hugging Face vs. PeopleOne

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

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

We are using [PeopleONE] to collect and manage our field data for payroll, invoicing, and production management purposes. So far, it works quite well for those uses. Additionally, we are using the app to manage communications from our offices to our field management at upper and middle field management levels. We have successfully used the application to communicate important upcoming events, COVID protocols and reporting processes, and other initiatives. I am unfamiliar with the limitations of this technology or applications for which it would be unsuited.

• 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

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

• The UI, both for desktop and mobile apps, is simple and virtually self-explanatory.
• Compared to apps we have used in the past, PeopleONE is fast, in both data entry and retrieval.
• The team responsible for creating our specific requirements for the app is exceptionally responsive. It is made up of creative problems solvers who have built a product that meets every need we have presented.

• 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

• We haven't actually experienced any issues of note to record here. Every concern, requirement, or change we have requested has been swiftly and satisfactorily resolved by the Impiger team.

[I give it this rating] because it has addressed all of our needs in a succinct manner and it operates efficiently.

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

• Improved accuracy of data collected
• Improved efficiency of data collected
• Improved efficiency of payroll and invoicing processes
• Decreased time, in the field and in the office, involved in managing data