Quickstart¶
Supported Tasks¶
Out of the box tasks you can solve with Backprop:
Conversational question answering in English (for FAQ chatbots, text analysis, etc.)
Text Classification in 100+ languages (for email sorting, intent detection, etc.)
Image Classification (for object recognition, OCR, etc.)
Text Vectorisation in 50+ languages (semantic search for ecommerce, documentation, etc.)
Summarisation in English (TLDRs for long documents)
Emotion detection in English (for customer satisfaction, text analysis, etc.)
Text Generation (for idea, story generation and broad task solving)
For more specific use cases, you can adapt a task with little data and a couple of lines of code using finetuning. We are adding finetuning support for all tasks soon.
Basic Task Solving¶
import backprop
context = "Take a look at the examples folder to see use cases!"
qa = backprop.QA()
# Start building!
answer = qa("Where can I see what to build?", context)
print(answer)
# Prints
"the examples folder"
See examples for all available tasks in Tasks.
Basic Finetuning and Uploading¶
from backprop.models import T5
from backprop import TextGeneration
tg = TextGeneration(T5, local=True)
# Any text works as training data
inp = ["I really liked the service I received!", "Meh, it was not impressive."]
out = ["positive", "negative"]
# Finetune with a single line of code
tg.finetune({"input_text": inp, "output_text": out})
# Use your trained model
prediction = tg("I enjoyed it!")
print(prediction)
# Prints
"positive"
# Upload to Backprop for production ready inference
# Describe your model
name = "t5-sentiment"
description = "Predicts positive and negative sentiment"
tg.upload(name=name, description=description, api_key="abc")
Learn more about finetuning in Finetuning.
Why Backprop?¶
No experience needed
Entrance to practical AI should be simple
Get state-of-the-art performance in your task without being an expert
Data is a bottleneck
Use AI without needing access to “big data”
With transfer learning, no data is required, but even a small amount can adapt a task to your niche.
There is an overwhelming amount of models
We implement the best ones for various tasks
A few general models can accomplish more with less optimisation
Deploying models cost effectively is hard work
If our models suit your use case, no deployment is needed
Adapt and deploy your own model with a couple of lines of code
Our API scales, is always available, and you only pay for usage