Update `README.md` with metadata
#1
by
alvarobartt
HF Staff
- opened
README.md
CHANGED
|
@@ -1,6 +1,14 @@
|
|
| 1 |
---
|
| 2 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
|
|
|
| 4 |
# Model Card for Dayhoff
|
| 5 |
|
| 6 |
Dayhoff is an Atlas of both protein sequence data and generative language models — a centralized resource that brings together 3.34 billion protein sequences across 1.7 billion clusters of metagenomic and natural protein sequences (GigaRef), 46 million structure-derived synthetic sequences (BackboneRef), and 16 million multiple sequence alignments (OpenProteinSet). These models can natively predict zero-shot mutation effects on fitness, scaffold structural motifs by conditioning on evolutionary or structural context, and perform guided generation of novel proteins within specified families. Learning from metagenomic and structure-based synthetic data from the Dayhoff Atlas increased the cellular expression rates of generated proteins, highlighting the real-world value of expanding the scale, diversity, and novelty of protein sequence data.
|
|
|
|
| 1 |
---
|
| 2 |
+
license: mit
|
| 3 |
+
pipeline_tag: text-generation
|
| 4 |
+
library_name: transformers
|
| 5 |
+
tags:
|
| 6 |
+
- protein-generation
|
| 7 |
+
- jamba
|
| 8 |
+
datasets:
|
| 9 |
+
- microsoft/Dayhoff
|
| 10 |
---
|
| 11 |
+
|
| 12 |
# Model Card for Dayhoff
|
| 13 |
|
| 14 |
Dayhoff is an Atlas of both protein sequence data and generative language models — a centralized resource that brings together 3.34 billion protein sequences across 1.7 billion clusters of metagenomic and natural protein sequences (GigaRef), 46 million structure-derived synthetic sequences (BackboneRef), and 16 million multiple sequence alignments (OpenProteinSet). These models can natively predict zero-shot mutation effects on fitness, scaffold structural motifs by conditioning on evolutionary or structural context, and perform guided generation of novel proteins within specified families. Learning from metagenomic and structure-based synthetic data from the Dayhoff Atlas increased the cellular expression rates of generated proteins, highlighting the real-world value of expanding the scale, diversity, and novelty of protein sequence data.
|