mims-harvard/ProCyon-Full

https://huggingface.co/mims-harvard/ProCyon-Full
Idleby mims-harvard011updated 1 year ago

ProCyon-Full is a multimodal foundation model for protein phenotypes, which combines a large language model with protein encoders to support inputs of interleaved free text and proteins. This model is instruction-tuned using the full ProCyon-Instruct dataset.

Sourced from

  • HuggingFace — mims-harvard/ProCyon-Full

Related resources

This Hugging Face repository stores the official resources for RAMER (reaction-aware multimodal enzyme function representation model).

Active04 months ago

Fine-tuned ESM-2 650M with LoRA for predicting protein subcellular localization (10 classes).

Active183 months ago
Python

esm3-sm-open-v1 is trained on 2.78 billion natural proteins. With synthetic data augmentation, this led to 3.15 billion protein sequences, 236 million protein structures, and 539 million proteins with function annotations, totaling 771 billion tokens.

Active2.1K4 months ago
Python

This set of model weights was released with the GitHub-compatible esm package format. The models here are kept for backwards compatibility, but we recommend you use the HuggingFace-compatible model weights at biohub/ESMC-6B (or biohub/ESMC-300M / biohub/ESMC-600M) instead.

Active1.1K4 months ago
Python

GeneLinguaLM is a multimodal model that generates natural language descriptions of protein functions from amino acid sequences.

Idle06 months ago

This set of model weights was released with the GitHub-compatible esm package format. The models here are kept for backwards compatibility, but we recommend you use the HuggingFace-compatible model weights at biohub/ESMC-6B (or biohub/ESMC-300M / biohub/ESMC-600M) instead.

Active6.2K5 months ago
Python