Help Lightning vs. Hugging Face

I think that there are different scenarios where the platform can be used, an example is the realization of remote consultancies, individually or in the group. In this sense, I must highlight that it is great whenever you need to work with other people while sharing information, videos, or specific content.

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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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• Sharing graphics, images and other resources.
• Connect remotely with different experts.
• Favors team work, even remotely.

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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 needs a strong network or signal connection.
• Nothing else.

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• 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 think it is very important to make it clear that most of these tools compliment and complement each other rather than oppose or surpass each other. In this sense, it is important to know when to apply one or the other, in addition to taking the time to get to know them thoroughly and master their functionalities. However, the different tools that Help Lightning contain put it above most platforms used for remote conferencing.

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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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• Makes work team better, even remotely.
• Allows to share important information and get constantly retro alimentations.
• Helps us to respect the Covid-19 prevention measures, while continue working.

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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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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