Weights & Biases
What is Weights & Biases?
Weights & Biases is a platform that offers developer tools specifically designed for machine learning. It helps developers track, visualize, and optimize machine learning experiments, making it easier to reproduce results and iterate on models.
How to use Weights & Biases?
To use Weights & Biases, developers need to sign up for an account on the website. Once registered, they can integrate Weights & Biases with their machine learning codebase using the provided Python library. Developers can then log, track, and visualize their machine learning experiments, keeping track of important metrics, hyperparameters, and model performance.
Weights & Biases's Core Features
{ "description": "Track and log machine learning experiments, keeping a record of important experiment details, hyperparameters, and metrics.", "feature_name": "Experiment Tracking" }
{ "description": "Visualize machine learning model architectures, performance metrics, and predictions to gain insights and improve model understanding.", "feature_name": "Model Visualization" }
{ "description": "Optimize models by efficiently searching for the best values of hyperparameters using advanced search algorithms and visualizations.", "feature_name": "Hyperparameter Tuning" }
Weights & Biases's Use Cases
{ "description": "Easily reproduce machine learning experiments by tracking all experiment parameters, code versions, and data sets used.", "use_case_name": "Reproducibility" }
{ "description": "Optimize machine learning models by visualizing model performance, identifying bottlenecks, and making informed adjustments.", "use_case_name": "Model Optimization" }
{ "description": "Facilitate collaboration among team members by sharing experiment results, visualizations, and insights with colleagues.", "use_case_name": "Collaboration" }
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Social Listening
Stable Diffusion Is Getting Outrageously Good!
❤️ Check out Fully Connected by Weights & Biases: https://wandb.me/papers W&B+Stable Diffusion: https://wandb.ai/capecape/stable_diffusions/reports/Speed-Up-Stable-Diffusion-on-Your-M1Pro-Macbook-Pro--VmlldzoyNjY0ODYz 📝 The paper "High-Resolution Image Synthesis with Latent Diffusion Models" is available here: https://arxiv.org/abs/2112.10752 Try it: Web 1: https://huggingface.co/spaces/stabilityai/stable-diffusion Web 2: https://beta.dreamstudio.ai/generate Web 3 (also Stable Diffusion XL!): https://clipdrop.co/stable-diffusion Web 4 (notebooks): https://github.com/TheLastBen/fast-stable-diffusion Guide: https://stable-diffusion-art.com/know-these-important-parameters-for-stunning-ai-images/#Sampling_methods Draw Things app: https://drawthings.ai/ Stable Diffusion Web UI: https://github.com/AUTOMATIC1111/stable-diffusion-webui Photoshop integration: http://stable.art Sources: Video https://twitter.com/dreamwieber/status/1618453304970997762 Photorealistic image: https://twitter.com/DiffusionPics/status/1619444407937241089 Realistic vision: https://civitai.com/models/4201?modelVersionId=29461 Infinite zoom: https://twitter.com/hardmaru/status/1612134809924685825 Tiled texture: https://stackoverflow.com/questions/24319825/texture-tiling-with-continuous-random-offset Stable.art (Photoshop): https://github.com/isekaidev/stable.art Wand - drawing: https://twitter.com/wand_app/status/1604186054923210752 Texturing: https://twitter.com/CarsonKatri/status/1600248599254007810 + https://twitter.com/CarsonKatri/status/1603419328019169280 AR + assistant: https://twitter.com/StrangeNative/status/1569700294673702912 Metahumans: https://twitter.com/CoffeeVectors/status/1569416470332858372 My latest paper on simulations that look almost like reality is available for free here: https://rdcu.be/cWPfD Or this is the orig. Nature Physics link with clickable citations: https://www.nature.com/articles/s41567-022-01788-5 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Jace O'Brien, Jack Lukic, John Le, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Martin, Matthew Valle, Michael Albrecht, Michael Tedder, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Richard Sundvall, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Twitter: https://twitter.com/twominutepapers Web: https://cg.tuwien.ac.at/~zsolnai/
NVIDIA’s AI Puts You In a Video Game 75,000x Faster!
❤️ Check out Microsoft Azure AI and try it out for free: https://azure.microsoft.com/en-us/solutions/ai 📝 The paper "Live 3D Portrait: Real-Time Radiance Fields for Single-Image Portrait View Synthesis " is available here: https://research.nvidia.com/labs/nxp/lp3d/ Fully Connected conference: https://wandb.ai/site/resources/events/fully-connected MKBHD, iJustine, Brian Tong persona source: https://www.youtube.com/watch?v=dtp6b76pMak 📝 My paper on simulations that look almost like reality is available for free here: https://rdcu.be/cWPfD Or this is the orig. Nature Physics link with clickable citations: https://www.nature.com/articles/s41567-022-01788-5 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Alex Balfanz, Alex Haro, B Shang, Benji Rabhan, Gaston Ingaramo, Gordon Child, John Le, Kyle Davis, Lukas Biewald, Martin, Michael Albrecht, Michael Tedder, Owen Skarpness, Richard Sundvall, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's research works: https://cg.tuwien.ac.at/~zsolnai/ Twitter: https://twitter.com/twominutepapers
OpenAI Sora Just Supercharged Filmmaking!
❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.me/papers The conference: https://wandb.ai/site/resources/events/fully-connected First impressions from creatives: https://openai.com/blog/sora-first-impressions 📝 My paper on simulations that look almost like reality is available for free here: https://rdcu.be/cWPfD Or this is the orig. Nature Physics link with clickable citations: https://www.nature.com/articles/s41567-022-01788-5 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Alex Balfanz, Alex Haro, B Shang, Benji Rabhan, Bret Brizzee, Gaston Ingaramo, Gordon Child, Jace O'Brien, John Le, Kyle Davis, Lukas Biewald, Martin, Michael Albrecht, Michael Tedder, Owen Skarpness, Richard Putra Iskandar, Richard Sundvall, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's research works: https://cg.tuwien.ac.at/~zsolnai/ Twitter: https://twitter.com/twominutepapers #openai #sora
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