From 8c84a320987e238edc01c6442d83a8ffb3e0ff2c Mon Sep 17 00:00:00 2001 From: www-data Date: Wed, 4 Dec 2024 22:28:11 +0000 Subject: [PATCH] add assets identified by bot --- assets/cognition.yaml | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/assets/cognition.yaml b/assets/cognition.yaml index b7acbd9c..6200cc7b 100644 --- a/assets/cognition.yaml +++ b/assets/cognition.yaml @@ -21,3 +21,31 @@ prohibited_uses: '' monitoring: '' feedback: none +- type: model + name: ESM Cambrian + organization: EvolutionaryScale + description: "ESM Cambrian is a next generation language model trained on protein sequences at the scale of life on Earth. ESM C models define a new state of the art for protein representation learning." + created_date: 2024-12-04 + url: https://www.evolutionaryscale.ai/blog/esm-cambrian + model_card: unknown + modality: + explanation: "Just as a person can fill in the blanks, such as: To __ or not to __ that is the ___ We can train language models to fill in the blanks. Except in biology, instead of training the model to predict words, we train it to predict the characters in a protein sequence, i.e. its sequence of amino acids." + value: text; text + analysis: "Evaluations. We use the methodology of Rao et al. to measure unsupervised learning of tertiary structure in the form of contact maps. A logistic regression is used to identify contacts. For a protein of length L, we evaluate the precision of the top L contacts (P@L) with sequence separation of 6 or more residues." + size: + explanation: "ESM C is trained at three scales: 300M, 600M, and 6B parameters." + value: 6B parameters + dependencies: [UniRef, MGnify, Joint Genome Institute] + training_emissions: unknown + training_time: unknown + training_hardware: unknown + quality_control: "ESM C was reviewed by a committee of scientific experts who concluded that the benefits of releasing the models greatly outweigh any potential risks." + access: + explanation: "ESM C is a drop-in replacement for previous models that provides major improvements in both capability and efficiency. ESM C models are available immediately for academic and commercial use under a new license structure designed to promote openness and enable scientists and builders." + value: open + license: unknown + intended_uses: "one that can be used by builders across a wide range of applications, to imbue AI models with a deeper understanding of the biology of life’s most important and mysterious molecules." + prohibited_uses: unknown + monitoring: unknown + feedback: unknown +