Update README.md

README.md

@@ -7,7 +7,7 @@ AIDO.RNA 650M is an RNA foundation model trained on 42 million non-coding RNA se
 #### Embedding
 ```python
 from genbio_finetune.tasks import Embed
-model = Embed.from_config({"model.backbone": "rnafm_650m_cds"}).eval()
+model = Embed.from_config({"model.backbone": "rnafm_650m"}).eval()
 collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
 embedding = model(collated_batch)
 print(embedding.shape)
@@ -17,7 +17,7 @@ print(embedding)
 ```python
 import torch
 from genbio_finetune.tasks import SequenceClassification
-model = SequenceClassification.from_config({"model.backbone": "rnafm_650m_cds", "model.n_classes": 2}).eval()
+model = SequenceClassification.from_config({"model.backbone": "rnafm_650m", "model.n_classes": 2}).eval()
 collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
 logits = model(collated_batch)
 print(logits)
@@ -27,7 +27,7 @@ print(torch.argmax(logits, dim=-1))
 ```python
 import torch
 from genbio_finetune.tasks import TokenClassification
-model = TokenClassification.from_config({"model.backbone": "rnafm_650m_cds", "model.n_classes": 3}).eval()
+model = TokenClassification.from_config({"model.backbone": "rnafm_650m", "model.n_classes": 3}).eval()
 collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
 logits = model(collated_batch)
 print(logits)
@@ -36,14 +36,14 @@ print(torch.argmax(logits, dim=-1))
 #### Regression
 ```python
 from genbio_finetune.tasks import SequenceRegression
-model = SequenceRegression.from_config({"model.backbone": "rnafm_650m_cds"}).eval()
+model = SequenceRegression.from_config({"model.backbone": "rnafm_650m"}).eval()
 collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
 logits = model(collated_batch)
 print(logits)
 ```
 #### Or use our one-liner CLI to finetune or evaluate any of the above!
 ```
-gbft fit --model SequenceClassification --model.backbone rnafm_650m_cds --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
-gbft test --model SequenceClassification --model.backbone rnafm_650m_cds --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
+gbft fit --model SequenceClassification --model.backbone rnafm_650m --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
+gbft test --model SequenceClassification --model.backbone rnafm_650m --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
 ```
 For more information, visit: [Model Generator](https://github.com/genbio-ai/modelgenerator)