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  1. README.md +9 -2
README.md CHANGED
@@ -41,7 +41,14 @@ pip install git+https://github.com/BiomedSciAI/biomed-multi-alignment.git
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  A simple example for a task already supported by `ibm/biomed.omics.bl.sm.ma-ted-400m`:
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  ```python
 
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  # Load Model
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  model = Mammal.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-400m.dti_bindingdb_pkd")
@@ -68,8 +75,8 @@ batch_dict = nn_model.forward_encoder_only([sample_dict])
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  batch_dict = DtiBindingdbKdTask.process_model_output(
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  batch_dict,
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  scalars_preds_processed_key="model.out.dti_bindingdb_kd",
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- norm_y_mean=norm_y_mean,
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- norm_y_std=norm_y_std,
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  )
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  ans = {
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  "model.out.dti_bindingdb_kd": float(batch_dict["model.out.dti_bindingdb_kd"][0])
 
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  A simple example for a task already supported by `ibm/biomed.omics.bl.sm.ma-ted-400m`:
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  ```python
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+ import os
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+ from fuse.data.tokenizers.modular_tokenizer.op import ModularTokenizerOp
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+ from fuse.data.utils.collates import CollateDefault
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+
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+ from mammal.examples.dti_bindingdb_kd.task import DtiBindingdbKdTask
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+ from mammal.keys import CLS_PRED, SCORES
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+ from mammal.model import Mammal
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  # Load Model
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  model = Mammal.from_pretrained("ibm/biomed.omics.bl.sm.ma-ted-400m.dti_bindingdb_pkd")
 
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  batch_dict = DtiBindingdbKdTask.process_model_output(
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  batch_dict,
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  scalars_preds_processed_key="model.out.dti_bindingdb_kd",
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+ norm_y_mean=5.79384684128215,
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+ norm_y_std=1.33808027428196,
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  )
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  ans = {
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  "model.out.dti_bindingdb_kd": float(batch_dict["model.out.dti_bindingdb_kd"][0])