Update README.md

README.md

@@ -18,8 +18,8 @@ mgen test --model SequenceClassification --model.backbone aido_dna_300m --data S
 ```python
 from modelgenerator.tasks import Embed
 model = Embed.from_config({"model.backbone": "aido_dna_300m"}).eval()
-collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
-embedding = model(collated_batch)
+transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
+embedding = model(transformed_batch)
 print(embedding.shape)
 print(embedding)
 ```
@@ -28,8 +28,8 @@ print(embedding)
 import torch
 from modelgenerator.tasks import SequenceClassification
 model = SequenceClassification.from_config({"model.backbone": "aido_dna_300m", "model.n_classes": 2}).eval()
-collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
-logits = model(collated_batch)
+transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
+logits = model(transformed_batch)
 print(logits)
 print(torch.argmax(logits, dim=-1))
 ```
@@ -38,8 +38,8 @@ print(torch.argmax(logits, dim=-1))
 import torch
 from modelgenerator.tasks import TokenClassification
 model = TokenClassification.from_config({"model.backbone": "aido_dna_300m", "model.n_classes": 3}).eval()
-collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
-logits = model(collated_batch)
+transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
+logits = model(transformed_batch)
 print(logits)
 print(torch.argmax(logits, dim=-1))
 ```
@@ -47,7 +47,7 @@ print(torch.argmax(logits, dim=-1))
 ```python
 from modelgenerator.tasks import SequenceRegression
 model = SequenceRegression.from_config({"model.backbone": "aido_dna_300m"}).eval()
-collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
-logits = model(collated_batch)
+transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
+logits = model(transformed_batch)
 print(logits)
 ```