Update README.md

README.md

@@ -8,11 +8,11 @@ tags:
 library_name: biomed
 license: apache-2.0
 base_model:
-- ibm/biomed.omics.bl.sm.ma-ted-400m
+- ibm/biomed.omics.bl.sm.ma-ted-458m
 ---
 
 Protein solubility is a critical factor in both pharmaceutical research and production processes, as it can significantly impact the quality and function of a protein.  
-This is an example for finetuning `ibm/biomed.omics.bl.sm-ted-400m` for protein solubility prediction (binary classification) based solely on the amino acid sequence.  
+This is an example for finetuning `ibm/biomed.omics.bl.sm-ted-458m` for protein solubility prediction (binary classification) based solely on the amino acid sequence.  
 
 The benchmark defined in: https://academic.oup.com/bioinformatics/article/34/15/2605/4938490  
 Data retrieved from: https://zenodo.org/records/1162886
@@ -28,13 +28,13 @@ Data retrieved from: https://zenodo.org/records/1162886
 
 ## Usage
 
-Using `ibm/biomed.omics.bl.sm.ma-ted-400m` requires installing [https://github.com/BiomedSciAI/biomed-multi-alignment](https://github.com/TBD)
+Using `ibm/biomed.omics.bl.sm.ma-ted-458m` requires installing [https://github.com/BiomedSciAI/biomed-multi-alignment](https://github.com/TBD)
 
 ```
 pip install git+https://github.com/BiomedSciAI/biomed-multi-alignment.git
 ```
 
-A simple example for a task already supported by `ibm/biomed.omics.bl.sm.ma-ted-400m`:
+A simple example for a task already supported by `ibm/biomed.omics.bl.sm.ma-ted-458m`:
 ```python
 import os
 
@@ -45,10 +45,10 @@ from mammal.keys import CLS_PRED, SCORES
 from mammal.model import Mammal
 
 # Load Model
-model = Mammal.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-400m.protein_solubility")
+model = Mammal.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-458m.protein_solubility")
 
 # Load Tokenizer
-tokenizer_op = ModularTokenizerOp.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-400m.protein_solubility")
+tokenizer_op = ModularTokenizerOp.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-458m.protein_solubility")
 
 # convert to MAMMAL style
 sample_dict = {"protein_seq": protein_seq}