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README.md

@@ -91,7 +91,7 @@ mgen test --model SequenceClassification --model.backbone aido_ragprotein_16b --
 ```python
 import torch
 from modelgenerator.tasks import Embed
-model = Embed.from_config({"model.backbone": "aido_protein_16b_ragplm"}).eval()
+model = Embed.from_config({"model.backbone": "aido_ragprotein_16b"}).eval()
 model.backbone.max_length = 12800
 data = torch.load("ModelGenerator/experiments/AIDO.RAGPLM/examples.pt", 'cpu')[0]
 transformed_batch = model.transform(data)
@@ -106,7 +106,7 @@ print(embedding.shape)
 ```python
 import torch
 from modelgenerator.tasks import SequenceClassification
-model = SequenceClassification.from_config({"model.backbone": "aido_protein_16b_ragplm", "model.n_classes": 2}).eval()
+model = SequenceClassification.from_config({"model.backbone": "aido_ragprotein_16b", "model.n_classes": 2}).eval()
 model.backbone.max_length = 12800
 data = torch.load("ModelGenerator/experiments/AIDO.RAGPLM/examples.pt", 'cpu')[0]
 transformed_batch = model.transform(data)
@@ -122,7 +122,7 @@ print(torch.argmax(logits, dim=-1))
 ```python
 import torch
 from modelgenerator.tasks import TokenClassification
-model = TokenClassification.from_config({"model.backbone": "aido_protein_16b_ragplm", "model.n_classes": 3}).eval()
+model = TokenClassification.from_config({"model.backbone": "aido_ragprotein_16b", "model.n_classes": 3}).eval()
 model.backbone.max_length = 12800
 data = torch.load("ModelGenerator/experiments/AIDO.RAGPLM/examples.pt", 'cpu')[0]
 transformed_batch = model.transform(data)
@@ -137,7 +137,7 @@ print(torch.argmax(logits, dim=-1))
 
 ```python
 from modelgenerator.tasks import SequenceRegression
-model = SequenceRegression.from_config({"model.backbone": "aido_protein_16b_ragplm"}).eval()
+model = SequenceRegression.from_config({"model.backbone": "aido_ragprotein_16b"}).eval()
 model.backbone.max_length = 12800
 data = torch.load("ModelGenerator/experiments/AIDO.RAGPLM/examples.pt", 'cpu')[0]
 transformed_batch = model.transform(data)