Hugging Face vs. IBM Cloud Functions

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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IBM Cloud Functions [is] not the worse product on the IBM cloud. I decided to write this review as I thought it would be balanced. I would still use functions to set up a serverless architecture where execution time is pretty quick and the code is relatively simple. I wouldn't use IBM Cloud Functions for async calls obviously, as costs could be higher. The functions documentation is lacking in terms of CI/CD, and there are unexplainable errors occurring - like the network connection that I mentioned. So I wouldn't just rely on IBM Cloud Functions too much for the entire system, but make sure it's diversified.

• 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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• Great substitute for a simple API calls to run non-complicated code.
• Easy way to run Python/Java/Javascript to get something done.
• File validation.

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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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• Billing can be a hassle, not the most responsive customer service/support team
• Handles & executes most functionalities, but other platforms offer more scalability if you're seeking consistent and stable growth

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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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• ICF is a lightweight service and does not require runtime configurations
• Scalable on demand and hence there is no need to pay for runtime costs

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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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• It directly affected our expenses since we do not need to deploy and maintain a set of separate applications.
• It allowed us to pay for only the amount of time cloud functions run.
• It saved on maintenance and monitoring of the applications it replaced.

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