Hugging Face vs. Thomson Reuters HighQ

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

HighQ Collaborate is well suited to situations where a law firm maintains numerous documents for a client and the client needs access to them on a regular basis. For example, we may store the client's minute book (which is relatively common for a large corporate law firm to do), but the client may need access to documents in that minute book on a regular basis. Likewise, we have an internal system at the firm for hosting digital versions of closing books, however, many clients would not have a similar system because they would only receive closing books irregularly. USBs get lost and the client might not want to put the closing book on the main server where anyone can access it. By putting the closing book on the extranet site, the individuals in the client's organization who should be able to access the closing book can do so.

Incentivized

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

Incentivized

• Document sharing. This product makes it easy to upload, review and organize documents related to a particular project or matter.
• Permissions. Collaborate allows very granular permissions to be assigned for shared documents and administrative activities such as workflows.
• Reliability. The product is cloud-based and rarely, if ever, unavailable.

Incentivized

• 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

• It is just not that exciting. We host documents on there for clients but the extranet sites have ultimately turned out to not be a product that our clients are clamoring for or that we are regularly pushing.

Incentivized

The interface is easy to use and overall the software seems pretty robust (I haven't had any crashes yet), so I haven't had to use the support very often. Likewise, I don't think I've ever had a client e-mail me with questions or issues - the software is pretty idiot-proof.

Incentivized

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

I feel that HighQ does not really have any real competition in this space because it simply accomplishes its goals far better than the competition at lower cost, while requiring less training and administration.

Incentivized

• 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

• Permits fairly simple administration by a single person for hundreds of Extranets
• One shop stopping for reliable, secure document sharing and signing with external parties
• Simple enough to use that internal and external users do not need training to take advantage of the product.

Incentivized