president?")    INFO | 2023-02-17 05:42:59,219 | Running _generate_text via gRPC    INFO | 2023-02-17 05:42:59,522 | Time to send message: 0.3 seconds    'john w. bush'You can send your pipeline directly over the wire to your model, but this will only work for small models (<2 Gb), and will be pretty slow:pipeline = load_pipeline()llm = SelfHostedPipeline.from_pipeline(    pipeline=pipeline, hardware=gpu, model_reqs=model_reqs)Instead, we can also send it to the hardware's filesystem, which will be much faster.rh.blob(pickle.dumps(pipeline), path="models/pipeline.pkl").save().to(    gpu, path="models")llm = SelfHostedPipeline.from_pipeline(pipeline="models/pipeline.pkl", hardware=gpu)PreviousReplicateNextSageMakerEndpointCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
The Runhouse allows remote compute and data across environments and users. See the Runhouse docs.
The Runhouse allows remote compute and data across environments and users. See the Runhouse docs. ->: president?")    INFO | 2023-02-17 05:42:59,219 | Running _generate_text via gRPC    INFO | 2023-02-17 05:42:59,522 | Time to send message: 0.3 seconds    'john w. bush'You can send your pipeline directly over the wire to your model, but this will only work for small models (<2 Gb), and will be pretty slow:pipeline = load_pipeline()llm = SelfHostedPipeline.from_pipeline(    pipeline=pipeline, hardware=gpu, model_reqs=model_reqs)Instead, we can also send it to the hardware's filesystem, which will be much faster.rh.blob(pickle.dumps(pipeline), path="models/pipeline.pkl").save().to(    gpu, path="models")llm = SelfHostedPipeline.from_pipeline(pipeline="models/pipeline.pkl", hardware=gpu)PreviousReplicateNextSageMakerEndpointCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.