Metadata-Version: 2.1
Name: backprop
Version: 0.0.1
Summary: Backprop
Home-page: https://github.com/kiri-ai/kiri
Author: Backprop
Author-email: hello@kiri.ai
License: UNKNOWN
Description: <h1 align="center">Backprop</h1>
        
        <p align="center">
           <a href="https://pypi.org/project/kiri/"><img src="https://img.shields.io/pypi/v/kiri"/></a> <img src="https://img.shields.io/pypi/pyversions/kiri"/> <a href="https://www.apache.org/licenses/LICENSE-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"/></a>
        </p>
        
        <p align="center">
        Kiri is a Python library that makes it simple to solve AI tasks without requiring any data.
        </p>
        
        Kiri is built around solving tasks with transfer learning. It implements state-of-the-art AI models that are general enough to solve real world tasks with no data required from the user.
        
        <p align="center">
           <img src=".github/kiri-example.png" width="600"/>
        </p>
        
        Out of the box tasks you can solve with Kiri:
        
        - 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.
        
        You can run all tasks locally or in production with our optimised inference [API](https://kiri.ai), where you only pay for usage. It includes all the tasks, models in our library and lets you upload your own finetuned models.
        
        | ⚡ [Getting started](#getting-started)                            | Installation, few minute introduction     |
        | :---------------------------------------------------------------- | :---------------------------------------- |
        | 💡 [Examples](https://github.com/kiri-ai/kiri/tree/main/examples) | Sample problems solved using Kiri         |
        | 📙 [Docs](https://kiri.readthedocs.io/en/latest/)                 | In-depth documentation for advanced usage |
        
        ## Getting started
        
        ### Installation
        
        Install Kiri via PyPi:
        
        ```bash
        pip install kiri
        ```
        
        ### Basic task solving
        
        ```python
        from kiri import Kiri
        
        context = "Take a look at the examples folder to see use cases!"
        
        # Use our inference API
        k = Kiri(api_key="abc")
        # Or run locally
        k = Kiri(local=True)
        
        # Start building!
        answer = k.qa("Where can I see what to build?", context)
        
        print(answer)
        # Prints
        "the examples folder"
        ```
        
        ### Basic finetuning and uploading
        
        ```python
        from kiri.models import T5
        from kiri.tasks 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(inp, out)
        
        # Use your trained model
        prediction = tg("I enjoyed it!")
        
        print(prediction)
        # Prints
        "positive"
        
        # Upload to Kiri for production ready inference
        import kiri
        
        model = tg.model
        # Describe your model
        model.name = "t5-sentiment"
        model.description = "Predicts positive and negative sentiment"
        
        kiri.upload(model, api_key="abc")
        ```
        
        ## Why Kiri?
        
        1. No experience needed
        
           - Entrance to practical AI should be simple
           - Get state-of-the-art performance in your task without being an expert
        
        2. 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.
        
        3. 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
        
        4. 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
        
        ## Examples
        
        Take a look at the [examples folder](https://github.com/kiri-ai/kiri/tree/main/examples).
        
        ## Documentation
        
        Check out our [docs](https://kiri.readthedocs.io/en/latest/).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
