Resource of free step by step video how to guides to get you started with machine learning.
Friday, April 22, 2022
LAION-5B: 5 billion image-text-pairs dataset (with the authors)
#laion #clip #dalle LAION-5B is an open, free dataset consisting of over 5 billion image-text-pairs. Today's video is an interview with three of its creators. We dive into the mechanics and challenges of operating at such large scale, how to keep cost low, what new possibilities are enabled with open datasets like this, and how to best handle safety and legal concerns. OUTLINE: 0:00 - Intro 1:30 - Start of Interview 2:30 - What is LAION? 11:10 - What are the effects of CLIP filtering? 16:40 - How big is this dataset? 19:05 - Does the text always come from the alt-property? 22:45 - What does it take to work at scale? 25:50 -When will we replicate DALL-E? 31:30 - The surprisingly efficient pipeline 35:20 - How do you cover the S3 costs? 40:30 - Addressing safety & legal concerns 55:15 - Where can people get started? References: LAION website: https://laion.ai/ LAION Discord: https://ift.tt/yE6LTaM LAION-5B: https://ift.tt/vpE4Cc0 img2dataset tool: https://ift.tt/AVxELkf LAION-400M: https://ift.tt/AQpCnYk Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/QndWaFZ BitChute: https://ift.tt/iceDLjA LinkedIn: https://ift.tt/mdLFEBo BiliBili: https://ift.tt/42EvIDB If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://ift.tt/vt8TxkY Patreon: https://ift.tt/NSwXsWE Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n
Subscribe to:
Post Comments (Atom)
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
Quick answer: Qwen 3 32B needs about 22.7 GB of VRAM at Q4_K_M with a 4k-token context — a used 24 GB card like the RTX 3090 is the minimu...
-
Inside TensorFlow: Summaries and TensorBoard [Collection] Take an inside look into the TensorFlow team’s own internal training sessions-...
-
Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml In this video we covered one of the most important question "COLLEGE KAB O...
-
Quick answer: DeepSeek V4 Flash is a Mixture-of-Experts model: all 284 billion parameters must be stored, so combined RAM plus VRAM — not ...
-
This video is a crash course on understanding how finetuning on LLM models can be performed uing QLORA,LORA, Quantization using LLama2, Grad...
-
In this video, you'll learn how to use machine learning, computer vision and deep learning to create a football analysis system. This pr...
-
Quick answer: For most learners, the best single machine learning book is Hands-On Machine Learning with Scikit-Learn, Keras & Tensor...
-
#minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command blocks. The n...
-
Quick answer: For an 8B model at Q4, local electricity costs roughly $0.05 per million output tokens — against about $0.53 per million ble...
No comments:
Post a Comment