{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"Provides pre-trained transformer protein language models (ESM-2, ESMFold, ESM-1v, MSA Transformer, ESM-IF1) for protein structure prediction, embedding generation, variant effect prediction, and inverse folding directly from sequence.","skillfed_tags":["protein-science","deep-learning","structure-prediction"],"use_cases":["Generate protein embeddings for downstream machine learning tasks like function prediction or homology detection","Predict 3D protein structures directly from amino acid sequences without multiple sequence alignments","Assess how amino acid substitutions affect protein function using zero-shot variant effect prediction","Design new protein sequences for a given 3D structure using inverse folding","Extract contact predictions and structural features from protein sequences for comparative analysis"],"what_it_does":"Fair-esm is a collection of pre-trained transformer models for protein sequence analysis from Facebook AI Research. It includes ESM-2 (a general-purpose protein language model available in multiple sizes), ESMFold (end-to-end structure prediction), ESM-1v (specialized for variant effect prediction), MSA Transformer (for multiple sequence alignment analysis), and ESM-IF1 (for inverse folding and sequence design). The models are trained on large-scale protein sequence datasets and can generate embeddings, predict 3D structures from sequences, assess the functional impact of mutations, and design new sequences for given protein structures.\n\nThe package is designed for researchers and practitioners working with protein analysis. It requires PyTorch (not declared as a dependency) and downloads pre-trained weights on first use. The repository is no longer actively maintained\u2014the last commit was February 2024 and the latest PyPI release is from November 2022\u2014so users should expect no updates, bug fixes, or support for new PyTorch versions.","worth_installing":"Yes, with conditions. The models are scientifically rigorous and widely cited, and the MIT license is permissive. However, the repository is archived and unmaintained since February 2024, so there will be no bug fixes or compatibility updates. Install only if you can tolerate a frozen codebase and are willing to manage PyTorch compatibility yourself. For active development or production systems requiring ongoing support, consider whether a maintained fork or alternative is available."},"id":"fair-esm","links":{"html":"https://skillfed.io/packages/fair-esm","md":"https://skillfed.io/packages/fair-esm.md","pypi":"https://pypi.org/project/fair-esm/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2022-11-01","license_spdx":null,"license_treatment":"permissive","name":"fair-esm","python_support":"unspecified","summary":"Evolutionary Scale Modeling (esm): Pretrained language models for proteins. From Facebook AI Research."},"popularity":{"monthly_downloads":170221,"position":10401,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.0"}