wehub-resource-sync
26 lines
680 B
Python
26 lines
680 B
Python
import transformers
|
|
|
|
import mlflow
|
|
|
|
conversational_pipeline = transformers.pipeline(model="microsoft/DialoGPT-medium")
|
|
|
|
with mlflow.start_run():
|
|
model_info = mlflow.transformers.log_model(
|
|
transformers_model=conversational_pipeline,
|
|
name="chatbot",
|
|
task="conversational",
|
|
input_example="A clever and witty question",
|
|
)
|
|
|
|
# Load the conversational pipeline as an interactive chatbot
|
|
|
|
chatbot = mlflow.pyfunc.load_model(model_uri=model_info.model_uri)
|
|
|
|
first = chatbot.predict("What is the best way to get to Antarctica?")
|
|
|
|
print(f"Response: {first}")
|
|
|
|
second = chatbot.predict("What kind of boat should I use?")
|
|
|
|
print(f"Response: {second}")
|