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serving-model-cards's Introduction

serving-model-cards

A collection of OSS models that are containerized and ready to be served in GCP's Vertex AI for easy deployment.

By using Vertex AI endpoints, users don't need to manage complex infrastructure to serve models.

Open in Cloud Shell

Make sure to read the permissable license for each model before use!!

Stable Diffusion
Generate images from a text prompt

FLAN-T5
Generate Text

Real-ESRGAN
Upscale images

BLIP
Image captioning

BART
Summarize Text

Instruct GPTJ
Instruction tune GPTJ

training-model-cards

A collection of OSS models that are containerized and ready to be trained in GCP's Vertex AI for easy deployment.

Train Dreambooth
Personalize stable diffusion

Finetune Stable Diffusion
Finetune stable diffusion

Image Segmentation
Create masks and inpaint

misc

A collection of different jobs and features.

Stable Diffusion Batch Job

Create a batch job with different styles
of stable diffusion

UI for Stable Diffusion Batch Job

Create a batch job with different styles
of stable diffusion

Large Scale Image Captioning with Dataflow

Caption millions of images at scale
using Dataflow

How to guides

serving-model-cards's People

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serving-model-cards's Issues

Training failed on TPUs for Dreambooth

Followed all instructions by the book, had images in a local images folder as-well. Training job stopped after 6 minutes with an error "replica workerpool0-0 exited with a non-zero status of 1", I had a TPU quota of 25 so they wouldn't run out as-well.

Screenshot of the Training Job from Console.
Screenshot 2023-03-17 at 2 33 09 AM

Here's a csv of logs for reference.
downloaded-logs-20230317-023353.csv

CLI command I've used to trigger the job.
python3.8 gcp_run_train.py --project-id=dreamboothtest --region=us-central1 --image-uri=gcr.io/dreamboothtest/training-dreambooth:latest --gcs-output-dir=gs://dreamboothmodelstore --instance-prompt="a photo of qw23 person" --hf-token="<>" --class-prompt="A photo of a person" --max-train-steps=800

please help

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