fix: Attention mask being None crashes distillation (#58)

model2vec/distill/inference.py

@@ -127,7 +127,13 @@ def create_output_embeddings_from_model_name(
     for batch_idx in tqdm(range(0, len(stacked), _DEFAULT_BATCH_SIZE)):
         batch = stacked[batch_idx : batch_idx + _DEFAULT_BATCH_SIZE].to(model.device)
         with torch.no_grad():
-            encoded: BaseModelOutputWithPoolingAndCrossAttentions = model(input_ids=batch.to(device))
+            # NOTE: we create these masks because nomic embed requires them.
+            # Normally, we could set them to None
+            token_type_ids = torch.zeros_like(batch)
+            attention_mask = torch.ones_like(batch)
+            encoded: BaseModelOutputWithPoolingAndCrossAttentions = model(
+                input_ids=batch.to(device), attention_mask=attention_mask, token_type_ids=token_type_ids
+            )
             out: torch.Tensor = encoded.last_hidden_state
             # NOTE: If the dtype is bfloat 16, we convert to float32,
             # because numpy does not suport bfloat16