Pre-trained models

Deploy a pre-trained model to kickstart your ML-powered application.
Baseten provides a growing set of pre-trained models that solve common ML tasks. These models are a great way to kickstart your ML application and showcase the features and functionality of Baseten - you can deploy pre-trained models along with optional application templates to add ML into your application in minutes.
Workspaces on the free Personal plan are limited to a single deployed model. Pre-trained models provided by Baseten do not count against this limit. To increase the number of models for your workspace, upgrade to a paid Baseten plan.
Pre-trained models offer many of the same features as your own models deployed on Baseten:
You can invoke the model directly through the Baseten Python client or an API call
You can create an application for the model
You can use the model in worklets
They come with editable readmes
Pre-trained models have some limitations that your models do not have:
You can't view health metrics or logs for pre-trained models
Pre-trained models do not have multiple versions
Pre-trained models have fixed model resources and auto-scaling settings
Pre-trained models do not count against the models limit in your workspace
Deployment
To deploy a pre-trained model, head to the Explore tab. Scroll through pre-trained models, filter by tags, or search for the model you want to deploy. Click on that model, then click "Deploy on Baseten" to deploy it.
Deploying a pre-trained model
By default, every pre-trained model comes with a starter application demonstrating how to use the model for a common use case. When you're in the deployment modal, you can opt out of creating this starter application by toggling off the "Create a starter application" option.
Once the model is deployed, you can edit the starter app or use the model in your applications.
Available models
Pre-trained models can be applied to common ML tasks. From speech transcription to sentiment analysis, image classification to photo restoration, pre-trained models deliver powerful ML capabilities directly to your applications. Baseten currently offers 24 pre-trained models:
​Whisper: Transcribe audio files.
​Stable Diffusion: Generate a novel image from a text prompt.
​Flan T5 XL: Generate sequences of text with a instruction-tuned LLM.
​Dall·E Mini: Generate a novel image from a text prompt.
​CodeGen mono 2B: Generate Python code from natural language or code prompts. This version of the model was fine-trained on Python code.
​CodeGen multi 2B: Generate Python code from natural language or code prompts. This version of the model was fine-trained on natural language and broad programming languages.
​GFP-GAN: Restore old photos.
​GPT-J: Generate text with GPT-J. This is an implementation of EleutherAI GPT-J-6B.
​Zero-shot classification: Classify snippets of text into unseen categories.
​Wav2vec 2.0 speech transcription: Transcribe audio files with wav2vec 2.0.
​CLIP: connecting text and images: Classify images with zero-shot-like functionality.
​Style transfer: Apply one image's style to another
​ResNet50 V2: Image detection model using ResNet V2 neural network architecture.
​Faster R-CNN Inception V2: Object detection model using Faster R-CNN with Inception.
​ELMo word representations: Generate embeddings from a language model trained on the 1 Billion Word Benchmark.
​Extractive question answering: Extract an answer from a given text when provided a question.
​Sentiment analyzer: Analyze sentiment in text.
​Text generation: Generate language given a prompt.
​Summarizer: Summarize a text into a shorter text.
​English to French translation: Translate between English and French.
​Masked language modeling: Fill a masked token in sequences based on the context around it.
​Token classification: Classify tokens in strings.
​Image segmentation: Identify classes of objects in an image.
​Iris random forest classifier: Predict Iris class with a random forest classifier.
​MNIST digit classifier: Logistic Regression model for classification of MNIST database of handwritten digits.
 
If you'd like Baseten to offer a specific pre-trained model, or if you'd like to fine-tune these models on your data, reach out.
 
Custom frameworks
Next - MODELS
Managing models
Last modified 2mo ago