Sold by: EvolutionaryScale, PBC
Deployed on AWS
The 300M version of ESM Cambrian; a protein language model that defines a new state of the art for protein representation learning.
Overview
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. ESM C models are a parallel model family to our flagship ESM3 generative models for programmable protein engineering. While ESM3 focuses on controllable generation of proteins for therapeutic and many other applications, ESM C focuses on creating representations of the underlying biology of proteins. ESM C scales up data and training compute to deliver dramatic performance improvements over ESM2.
Highlights
- The 300M version of ESM Cambrian; a protein language model that defines a new state of the art for protein representation learning.
Details
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Dimensions summary
This listing is free to use, so the four dimensions carry no software charge. Each dimension reflects a way to run model inference on AWS SageMaker, billed by host hours. You pick between two instance sizes: ml.g5.2xlarge or ml.g5.4xlarge. For each size, you also choose a mode: batch or real-time. Batch mode processes grouped requests, while real-time mode handles live requests. Your cost depends on which instance size and mode you select, plus how many hours you run it.
Top-of-mind questions for buyers
You pay for the AWS SageMaker instance that runs model inference. The ml.g5.2xlarge and ml.g5.4xlarge are GPU-backed instance types, with the ml.g5.4xlarge providing more compute and memory. You are billed per host hour the instance runs, regardless of how many requests it processes.
Billing is per host hour the instance runs. This software listing is free, so no software charge applies. Real-time endpoints accrue AWS instance charges while active, even when idle. Batch jobs run only for the duration of the task. Stopping the instance ends host-hour charges.
Batch mode processes grouped requests, so the instance runs only during the job and stops afterward. Real-time mode keeps an endpoint running to handle live requests, accruing host hours the whole time it stays up. Batch suits scheduled workloads; real-time suits continuous, on-demand inference.
evolutionaryscale.ai
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bugfixes: reduce gpu imprecision, fix list encoding bug
Additional details
Inputs
- Summary
Please refer to our documentation at https://github.com/evolutionaryscale/esm
- Input MIME type
- application/json
https://github.com/evolutionaryscale/esm
https://github.com/evolutionaryscale/esm
Resources
Vendor resources
Support
Vendor support
You can read our documentation at https://github.com/evolutionaryscale/esm or view our detailed docs at https://forge.evolutionaryscale.ai/reference .
Email support@evolutionaryscale.ai if you need dedicated help.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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The 600M version of ESM Cambrian; a protein language model that defines a new state of the art for protein representation learning.
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