Hugging Face vs. Yamdu

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

Even for a small business like mine, Yamdu really felt like a one-stop shop for everything. It's hard to find a comprehensive software for film/video productions, but Yamdu has everything we need. The only thing that really held us back was the cost, ultimately. If anything, I would love a storyboarding feature that let you set the time per shot and build out a sequence in pre-production. I used Storyboarder for this currently and it's very helpful, especially for music videos, to be able to build out a storyboard, set a music/audio track to it, then play it back in real time and see the pacing of the shoot.

• 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

• Crewlists
• Callsheets
• Breakdowns

• 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

• More specific financial management reports.
• Creation of some instant messaging software for the team.

What you see is what you get. It's easy to start working when you setup your first project. Also team members do not need many new to learn skills to work with the basic functions. Really incredible is Yamdu's help center. It is always available in the right corner. A lot of topics are covered with video links. If you need personal assistance, you can write a message within the help-box and Yamdu's crew is really fast in responding!

This is one of Yamdu's strongest points.

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

At the time, there really wasn't anything else like Yamdu. Especially as, in Celtx's case, at that time they weren't doing Excel/CSV exports of shot lists in the A/V format, something we required for what we were shooting. I understand that StudioBinder has increased its featureset the past few years, but Yamdu always felt like the most robust option and more familiar with the film/tv world.

• 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

• Positive impact, centralized place with some good tools for film productions
• Negative impact, not that flexible and as expected and strict pricing policy with little flexibility