ESM2 Finetuning refactor

docs/docs/user-guide/getting-started/development.md

@@ -136,7 +136,7 @@ of the model. The fine-tuning steps will be application-specific, but a general
 6. **Run inference**: Once the model is fine-tuned, use it to make predictions on new, unseen data.
 
 For more information on fine-tuning a model, refer to the [ESM-2 Fine-tuning
-Tutorial](../examples/bionemo-esm2/finetune.md).
+Tutorial](../examples/bionemo-esm2/finetune.ipynb).
 
 ## Advanced Developer Documentation
 

sub-packages/bionemo-esm2/pyproject.toml

@@ -22,6 +22,7 @@ bionemo-esm2-train= "bionemo.esm2.run.main:main"
 bionemo-esm2-recipe= "bionemo.esm2.run.recipes:main"
 infer_esm2 = "bionemo.esm2.scripts.infer_esm2:infer_esm2_entrypoint"
 train_esm2 = "bionemo.esm2.scripts.train_esm2:train_esm2_entrypoint"
+finetune_esm2 = "bionemo.esm2.scripts.finetune_esm2:finetune_esm2_entrypoint"
 
 # Make sure that the tokenizer files are included along with the python files during installation.
 [tool.setuptools.package-data]