Contrastive Learning has been shown to be an effective way to learn representations for various tasks. This post summarized some of the important papers for this method.
blog.samaya.tech/2022/04/Contra…#DeepLearning
An open-source solution has a 25% better accuracy than Amazon Forecast and is 20% more accurate than fbprophet. It also performs 4x faster than Amazon Forecast and is less expensive.
github.com/Nixtla/nixtla#MachineLearning
Terraform is a powerful tool for building, changing, and versioning infrastructure. With its infrastructure as code approach, execution plans, and resource graph, Terraform is a must-have for any #infrastructure engineer!
github.com/hashicorp/terr…#openSource#backend
Fine-Tuning with Hugging Face Trainer. Check out my video tutorial to learn how you can improve and simplify ML model fine-tuning workflow with Hugging Face Trainer. This API is very well defined. @huggingface rocks 🚀
Video: youtu.be/L6Dr8AFXMd8
Code: github.com/katanaml/sparr…
LMs can learn via inference alone through demonstrations -- but how does it work?
We find that LMs do not really need correct input-output pairs. Randomly replacing labels in the demonstrations barely hurts performance, consistently over 12 models.
arxiv.org/abs/2202.12837
We’re pleased to announce new advances in SEER, Meta AI’s groundbreaking self-supervised #computervision model. SEER is now not only much more powerful, it also produces fairer, more robust computer vision models. Learn more:
ai.facebook.com/blog/seer-10b-…
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