Issue while doing predict_proba with new release of setfit

[anjibabupalla]

We have finetuned the paraphrase-mpnet-base-v2 using setfit 1.0.3 and I have upgraded the setfit ==1.1.2 when I load the model it is throwing me the error
AttributeError: 'SentenceTransformer' object has no attribute 'default_prompt_name'

Code:

with open('v1.pkl', 'rb') as f:
    model = pickle.load(f)

def predict_proba(texts, model):
    return model.predict_proba(texts)

# Predicting top 3 probabilities
test_df['predicted_probas'] = test_df.apply(
    lambda x: pd.Series(predict_proba([x.Text], model)[0]).nlargest(3).values.tolist(), 
    axis=1
)

Full trace:

AttributeError: 'SentenceTransformer' object has no attribute 'default_prompt_name'
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
File <command-8842824531215917>, line 7
      4     return model.predict_proba(texts)
      6 # Predicting top 3 probabilities
----> 7 test_df['predicted_probas'] = test_df.apply(
      8     lambda x: pd.Series(predict_proba([x.Text], model)[0]).nlargest(3).values.tolist(), 
      9     axis=1
     10 )

File /databricks/python/lib/python3.10/site-packages/pandas/core/frame.py:8848, in DataFrame.apply(self, func, axis, raw, result_type, args, **kwargs)
   8837 from pandas.core.apply import frame_apply
   8839 op = frame_apply(
   8840     self,
   8841     func=func,
   (...)
   8846     kwargs=kwargs,
   8847 )
-> 8848 return op.apply().__finalize__(self, method="apply")

File /databricks/python/lib/python3.10/site-packages/pandas/core/apply.py:733, in FrameApply.apply(self)
    730 elif self.raw:
    731     return self.apply_raw()
--> 733 return self.apply_standard()

File /databricks/python/lib/python3.10/site-packages/pandas/core/apply.py:857, in FrameApply.apply_standard(self)
    856 def apply_standard(self):
--> 857     results, res_index = self.apply_series_generator()
    859     # wrap results
    860     return self.wrap_results(results, res_index)

File /databricks/python/lib/python3.10/site-packages/pandas/core/apply.py:873, in FrameApply.apply_series_generator(self)
    870 with option_context("mode.chained_assignment", None):
    871     for i, v in enumerate(series_gen):
    872         # ignore SettingWithCopy here in case the user mutates
--> 873         results[i] = self.f(v)
    874         if isinstance(results[i], ABCSeries):
    875             # If we have a view on v, we need to make a copy because
    876             #  series_generator will swap out the underlying data
    877             results[i] = results[i].copy(deep=False)

File <command-8842824531215917>, line 8, in <lambda>(x)
      4     return model.predict_proba(texts)
      6 # Predicting top 3 probabilities
      7 test_df['predicted_probas'] = test_df.apply(
----> 8     lambda x: pd.Series(predict_proba([x.Text], model)[0]).nlargest(3).values.tolist(), 
      9     axis=1
     10 )

File <command-8842824531215917>, line 4, in predict_proba(texts, model)
      2 def predict_proba(texts, model):
      3     # Assuming model has a method predict_proba
----> 4     return model.predict_proba(texts)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-f8054330-4852-4683-b8e1-f27677fba16f/lib/python3.10/site-packages/setfit/modeling.py:514, in SetFitModel.predict_proba(self, inputs, batch_size, as_numpy, show_progress_bar)
    512 if is_singular:
    513     inputs = [inputs]
--> 514 embeddings = self.encode(inputs, batch_size=batch_size, show_progress_bar=show_progress_bar)
    515 probs = self.model_head.predict_proba(embeddings)
    516 if isinstance(probs, list):

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-f8054330-4852-4683-b8e1-f27677fba16f/lib/python3.10/site-packages/setfit/modeling.py:451, in SetFitModel.encode(self, inputs, batch_size, show_progress_bar)
    436 def encode(
    437     self, inputs: List[str], batch_size: int = 32, show_progress_bar: Optional[bool] = None
    438 ) -> Union[torch.Tensor, np.ndarray]:
    439     """Convert input sentences to embeddings using the `SentenceTransformer` body.
    440 
    441     Args:
   (...)
    449         torch Tensor if this model has a differentiable Torch head, or otherwise as a numpy array.
    450     """
--> 451     return self.model_body.encode(
    452         inputs,
    453         batch_size=batch_size,
    454         normalize_embeddings=self.normalize_embeddings,
    455         convert_to_tensor=self.has_differentiable_head,
    456         show_progress_bar=show_progress_bar,
    457     )

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-f8054330-4852-4683-b8e1-f27677fba16f/lib/python3.10/site-packages/torch/utils/_contextlib.py:116, in context_decorator.<locals>.decorate_context(*args, **kwargs)
    113 @functools.wraps(func)
    114 def decorate_context(*args, **kwargs):
    115     with ctx_factory():
--> 116         return func(*args, **kwargs)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-f8054330-4852-4683-b8e1-f27677fba16f/lib/python3.10/site-packages/sentence_transformers/SentenceTransformer.py:987, in SentenceTransformer.encode(self, sentences, prompt_name, prompt, batch_size, show_progress_bar, output_value, precision, convert_to_numpy, convert_to_tensor, device, normalize_embeddings, truncate_dim, pool, chunk_size, **kwargs)
    983         except KeyError:
    984             raise ValueError(
    985                 f"Prompt name '{prompt_name}' not found in the configured prompts dictionary with keys {list(self.prompts.keys())!r}."
    986             )
--> 987     elif self.default_prompt_name is not None:
    988         prompt = self.prompts.get(self.default_prompt_name, None)
    989 else:

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-f8054330-4852-4683-b8e1-f27677fba16f/lib/python3.10/site-packages/torch/nn/modules/module.py:1940, in Module.__getattr__(self, name)
   1938     if name in modules:
   1939         return modules[name]
-> 1940 raise AttributeError(
   1941     f"'{type(self).__name__}' object has no attribute '{name}'"
   1942 )

AttributeError: 'SentenceTransformer' object has no attribute 'default_prompt_na