Added support for bfloat16 to zero-shot classification pipeline (hugg…

…ingface#33554)

* Added support for bfloat16 to zero-shot classification pipeline

* Ensure support for TF.

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Remove dependency on `torch`.

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

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Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

src/transformers/pipelines/zero_shot_classification.py

@@ -239,7 +239,10 @@ def _forward(self, inputs):
     def postprocess(self, model_outputs, multi_label=False):
         candidate_labels = [outputs["candidate_label"] for outputs in model_outputs]
         sequences = [outputs["sequence"] for outputs in model_outputs]
-        logits = np.concatenate([output["logits"].numpy() for output in model_outputs])
+        if self.framework == "pt":
+            logits = np.concatenate([output["logits"].float().numpy() for output in model_outputs])
+        else:
+            logits = np.concatenate([output["logits"].numpy() for output in model_outputs])
         N = logits.shape[0]
         n = len(candidate_labels)
         num_sequences = N // n