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Weights & Biases Reviews & Product Details - Page 4

Weights & Biases Overview

What is Weights & Biases?

Weights & Biases is the leading AI developer platform supporting end-to-end MLOps and LLMOps workflows. Trusted by over 30 foundation model builders and 1,000 companies to productionize machine learning at scale including teams at OpenAI, Toyota, and Microsoft, Weights & Biases is part of the new standard of best practices for generative AI and machine learning.

Weights & Biases Details
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Product Description

Record and visualize every detail of your research, collaborate easily, advance the state of the art


Seller Details
Year Founded
2017
HQ Location
San Francisco, California, United States
Twitter
@weights_biases
43,462 Twitter followers
LinkedIn® Page
www.linkedin.com
288 employees on LinkedIn®
Description

Weights & Biases: the AI developer platform.Build better models faster, fine-tune LLMs, develop GenAI applications with confidence, all in one system of record developers are excited to use. W&B Models is the MLOps solution used by foundation model builders and enterprises who are training, fine-tuning, and deploying models into production. W&B Weave is the LLMOps solution for software developers who want a lightweight but powerful toolset to help them track and evaluate LLM applications.Weights & Biases is trusted by over a 1,000 companies to productionize AI at scale including teams at OpenAI, Meta, NVIDIA, Cohere, Toyota, Square, Salesforce, and Microsoft. Sign up for a 30-day free trial today at http://wandb.me/trial.


Kevin  F.
KF
Overview Provided by:

Recent Weights & Biases Reviews

Simon S.
SS
Simon S.Small-Business (50 or fewer emp.)
4.5 out of 5
"Review for wandb"
I like the flexibility to log custom parameters, and the colorful comparisons between models in for instance confusion matrices.
Verified User
U
Verified UserEnterprise (> 1000 emp.)
5.0 out of 5
"The fastest way to log your training runs"
Everything works almost out of the box and it has a "nice look" once logged in
Verified User
U
Verified UserSmall-Business (50 or fewer emp.)
5.0 out of 5
"Great platform for DNN training support"
Visualization of data from different perspective
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Weights & Biases Media

Weights & Biases Demo - Tables
Tables can be used to visualize data in any format, intuitively enabling a better understanding of model performance.
Weights & Biases Demo - Tables
Tables are the best way to visualize and analyze model predictions, making it easier than ever to evaluate your models.
Weights & Biases Demo - Experiment Tracking
Track and visualize live metrics such as training loss and GPU utilization to identify bottlenecks and optimize model performance.
Weights & Biases Demo - Dashboard
Dashboard is your central home for understanding your experiments. Compare the performance of different models and obtain a deep understanding of key metrics and more.
Weights & Biases Demo - Reports
Reports make collaboration straightforward and enjoyable - enabling you to share live updates about your experiments and work together with colleagues across the world via live commenting.
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41 Weights & Biases Reviews

4.7 out of 5
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41 Weights & Biases Reviews
4.7 out of 5
41 Weights & Biases Reviews
4.7 out of 5

Weights & Biases Pros and Cons

How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Cons

Overall Review Sentiment for Weights & BiasesQuestion

Time to Implement
<1 day
>12 months
Return on Investment
<6 months
48+ months
Ease of Setup
0 (Difficult)
10 (Easy)
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Ian T.
IT
Founder/CEO
Small-Business(50 or fewer emp.)
More Options
Validated Reviewer
Review source: Organic
What do you like best about Weights & Biases?

This is the rare product that both engineers and researchers love, and it has been transformative for our team's ability to work on large, complex problems together. In particular, the Reports feature has become our main medium for collaboration, almost more essential than Github. It makes it easy to keep a shared ground truth for baselines while enabling everyone to fork their own versions. You can pull in as much or as little of the other team members’ work to your own current workspace and Reports – the filtering by tag, time, etc. makes this easy. We primarily use tags to make runs available with a quick semantic hook.

The ability to create custom visualizations (via Vega) and filter across many runs during sweeps has been very useful. We’ve made everything from embedding projections (tsne/umap) to sweep overviews here, and then been able to share them for everyone to use. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

I was pretty skeptical initially that it would help to have more collaborative visualization tools beyond Tensorboard, etc – and I was completely wrong! I wish I’d realized this sooner, wandb seems to know the current flaws in our workflow better than we do :) Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Wandb has been key for us to find regressions or mistakes that might have taken months to uncover without it (or never found them at all!). Many of the biggest advances in generative modeling that we've seen in the last 5 years (language models, text-to-image) were made by teams using wandb, and I wouldn't be surprised if the field was nearly a year behind its current frontier if wandb didn't exist. Especially for generative modeling, visualization and tracking is so essential that it saves you time you didn't realize you were wasting (both in experimental mistakes and collaboration/communication cost). None of the other tools we've tried (Tensorboard and similar) or experiment tracking systems we've built internally have been nearly as good as wandb for this. Also, logging/experiment tracking/visualization is surprisingly difficult to get right as you scale in team and model complexity, so the fact that wandb is very simple to integrate into any codebase makes one almost forget how much it is handling. Review collected by and hosted on G2.com.

John L.
JL
Staff Engineer
Enterprise(> 1000 emp.)
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Validated Reviewer
Verified Current User
Review source: Organic
Business partner of the seller or seller's competitor, not included in G2 scores.
What do you like best about Weights & Biases?

I like that W&B provides an on-premise solution (in our cloud environment) that allows us to manage our data completely internally. Their python library is easy to use and can integrate quickly with our existing workflows for ML research. Specifically, we're able to automatically collect relevant ML data and display appropriate visualizations to help us find the best models. More generally, W&B lets us better keep track of our models and test various experiments easily.

They have a great reporting feature as well, where we can easily create and share reports relating to our ML experiments. The visualizations also flexible, and we can basically create whatever visuals we want (although with some effort)

I also like that they keep adding more features to help us accelerate and manage all of our ML operations easily. To my knowledge, we haven't made use of all of these features yet (at least Artifacts and Tables), but they will definitely help us with our workflows as we grow and mature our teams. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Since we're running on-premise in our cloud, it takes a little effort to maintain the product in our environment. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Solves where to track machine learning experiments, by providing a single environment for research results to be collected and displayed. This helps our researchers be more productive at doing ML research and finding the best models for our problems. Review collected by and hosted on G2.com.

CP
Director, Computer Vision and Machine Learning
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Verified Current User
Review source: Organic
What do you like best about Weights & Biases?

Wandb allows my team to collaborate and share information. As soon as we became users of the tool I noticed that we would spend time analyzing the training loss graphs for model runs, and asking each other for help. These runs used to be squirrelled away on people's desktop machines, and were nearly impossible to reconstruct old runs. Now we can look at older runs very easily and our team can collaborate on experiment results. The support from the wandb team has been amazing too. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

nothing really missing in my opinion. I would like to be able to administer my account a little easier, like seeing how many seats I have left and which users are dormant would allow me to manage my license pool more effectively. Review collected by and hosted on G2.com.

Recommendations to others considering Weights & Biases:

I highly recommend it. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

It gets our engineers collaborating more and speeds up the team, Training these models can be very tricky and have more people analyzing the results from a run really helps us to save time and accelerates our development. Also tracking historical runs is very handy too. Review collected by and hosted on G2.com.

Verified User in Computer Hardware
AC
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Verified Current User
Review source: Organic
What do you like best about Weights & Biases?

The quality of the features on wandb is always very high. We use metrics, artifact management, and hyperparameter sweep extensively and find that wanbd fits seamlessly with our training. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

wandb is developing their feature set but doesn't yet have a complete solution to all of ML Ops. That means I still have to find other tools to fill the gaps. Usually wandb integrates well with these tools but the integration always requires work. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

wandb helps me track and manage my ml processing jobs and artifacts. Without them I would have to stitch together multiple other tools or write my own ad-hoc versions of things. wandb definitely helps by automating the most tedious parts of my processing so I can do more high-value work. Review collected by and hosted on G2.com.

Verified User in Renewables & Environment
UR
Small-Business(50 or fewer emp.)
More Options
Validated Reviewer
Review source: Organic
What do you like best about Weights & Biases?

W&B is an excellent tool, particularly for collaborating on and maintaining a record of machine learning experiments. I think its role is in closing the gap between training and analysis, which it does very well. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

* Reports performance can be slow at times for a large number of displayed runs (e.g. 300-600)

* Tools such as Sweeps don't allow for an alternative backend, and available frontend tools are somewhat clunky without specific customization towards the end use (e.g. using reports for analyzing tune results). As it exists now, I think W&B offers more to ML teams that don't have a supporting SW infrastructure team. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

* Experiment tracking

* Quickly performing basic analysis early on in experiments Review collected by and hosted on G2.com.

Dwight C.
DC
Co-Founder & Chairman of the Board
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Review source: Organic
What do you like best about Weights & Biases?

Weights and Biases makes our entire workflow easier. It biases new (and sometimes seasoned!) engineers toward better best practices, makes it easier to introspect, improve, store, and serve models - it makes the entire process better. Can't recommend highly enough! Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Really can't think of anything. Wish they'd ship even more new features faster; the ones they've added recently are spectacular! Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Weights and Biases makes training, introspecting & improving, storing, and serving models easier. It improves the workflow of our entire machine learning engineering team. Review collected by and hosted on G2.com.

Adrien G.
AG
Head of ML
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Review source: Organic
What do you like best about Weights & Biases?

W&B is the best platform to support experimental workflows in ML. Rapid turn-around time and extensive experimentation is key to identify what works best, but you also need to keep track and motivate your choices before deploying, especially for safety-critical areas like automomous driving and robotics. W&B enables both: massive experimentation and clear management. Plus having everything in the browser, shareable, and with deep introspection capabilities is a huge productivity boost for any collaborative project. My team and I have been using it since day 1 and we can't live without it! Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Nothing! The team just keeps adding features and responds really quickly to any of our bug reports. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Experimentation at scale, hyperparameter search, traceability, research exploration, continuous training and deployment of models. Review collected by and hosted on G2.com.

Naman G.
NG
Teaching Assistant
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Review source: G2 invite
Incentivized Review
What do you like best about Weights & Biases?

Support almost all kind of frameworks whether it is pytorch or tensorflow on any other . It integrates very easily with other and collaborative in the real time . Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Nothing to be disliked about in the application. I can just say i can be more user friendly and interactive. I find some operation that can be very simple but are difficult to use . Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Solving most of my machine learning projects problems as there are very good tools available in the application. I personally use tensorflow framework and it quite easy to use and has many easy tools available. Review collected by and hosted on G2.com.

LP
Senior Data Scientist
More Options
Validated Reviewer
Review source: Organic
What do you like best about Weights & Biases?

The simplicity of integrating wandb into our pipelines and experiments Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Nooooooooooooooooooooooooooooooooooothing Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

It takes away a lot of work in regards to versioning artifacts, which makes our team a lot more productive Review collected by and hosted on G2.com.

Verified User in Computer Software
UC
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Verified Current User
Review source: Organic
What do you like best about Weights & Biases?

Our main use case for W&B is tracking experiments and sharing them in the team. It's super easy to set up and share experiments. Review collected by and hosted on G2.com.

What do you dislike about Weights & Biases?

Sometimes the UI is a bit slow, but not slow enough that it breaks our workflow. That's the only improvement area I can think of. Review collected by and hosted on G2.com.

What problems is Weights & Biases solving and how is that benefiting you?

Tracking and sharing model training experiments. The reports feature is also super useful for collecting the results in one place. Review collected by and hosted on G2.com.