chore: import upstream snapshot with attribution

examples/transformers/simple.py

@@ -0,0 +1,31 @@
+import transformers
+
+import mlflow
+
+task = "text-generation"
+
+generation_pipeline = transformers.pipeline(
+    task=task,
+    model="gpt2",
+)
+
+input_example = ["prompt 1", "prompt 2", "prompt 3"]
+
+parameters = {"max_length": 512, "do_sample": True}
+
+with mlflow.start_run() as run:
+    model_info = mlflow.transformers.log_model(
+        transformers_model=generation_pipeline,
+        name="text_generator",
+        input_example=(["prompt 1", "prompt 2", "prompt 3"], parameters),
+    )
+
+sentence_generator = mlflow.pyfunc.load_model(model_info.model_uri)
+
+print(
+    sentence_generator.predict(
+        ["tell me a story about rocks", "Tell me a joke about a dog that likes spaghetti"],
+        # pass in additional parameters applied to the pipeline during inference
+        params=parameters,
+    )
+)