Local LLMs

Build locally-hosted LLMs using top machine learning libraries like PyTorch, TensorFlow, NLTK, HuggingFace, etc. with 100% no-code.

TRUSTED BY 10,000+ GLOBAL ORGANISATIONS

Marsupy

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Build local LLMs using top data science libraries

If you are totally dependent on OpenAI’s API key to power your AI apps, not only you lack most of the features that other platforms offers, but you are also at a high risk of being vanished if they decide to increase the API cost (like what Twitter did few weeks earlier). And this is yet not the end, you are always at a risk of breach of data laws and confidentiality. (Read how OpenAI’s new data laws are nothing but thin air : https://sttabot.io/openais-data-… ) Now, when we launched Supervised (Sttabot v2.0), one user pointed out this issue and suggested to work on a tech called Local LLMs. Over the time, we worked on it and built this product. This is way simple but revolutionary where you can currently build AI apps using what more is offered by OpenAI or deepmind. In coming updates, we are planning to introduce two major things in Local LLMs – ‘On-site deployment’ and ‘LLAMA integration’. Currently, the AI you build, has to be deployed on services like PyScript.com (don’t worry, we have already pulled a detailed installation instruction up there). However, in coming updates, we will let you deploy your AI on cloud from Sttabot only. Second, we are yet to train the model to build AI apps using LLAMA. This will be breakthrough because of its potential and open source nature. We will also add this in coming updates. So far, Local LLMs have been tested to 210 users at Sttabot and is rated a whooping 4.9/5.0. With this release, the feature will be public for all our 10,000+ users as well as for those who are trying Sttabot for the first time.

Opensource

Most libraries of Local LLMs are open source. So, you owns your data, not some big tech firm.

Locally Hosted

Each bot can be locally hosted over your favourite hosting provider or on Pyscript.com

Used by Top Data Scientists

Libraries in Local LLMs are utilised by top data scientists to build complex LLMs.

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Pricing

You need to buy a paid plan to use recommendation engine.

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Use Cases

Data Privacy and Security

Local LLMs could be crucial in scenarios where data privacy is paramount. Industries dealing with sensitive information like healthcare, legal, or finance might prefer locally-hosted models to ensure that data remains within their secure environments.

Real-time Applications with Low Latency

Applications that require real-time responses, such as interactive virtual assistants or gaming, can benefit from locally-hosted models that reduce latency compared to sending requests to cloud servers.

Limited Internet Connectivity

In areas with limited or unreliable internet connectivity, Local LLMs can provide a more consistent and reliable experience since they don’t rely on external cloud services.

Edge Computing Devices

Devices at the edge of the network, like IoT devices and embedded systems, can make use of Local LLMs to perform language-related tasks without needing to send data to the cloud, which can be advantageous in terms of both speed and privacy.

Confidential Data Analysis

Local LLMs could assist in analyzing confidential or proprietary text data without exposing it to external servers. This could be beneficial for market analysis, legal document review, or competitive intelligence.

Regulatory Compliance

Industries subject to strict regulatory compliance, such as legal or healthcare, could utilize Local LLMs to ensure that data stays within the organization’s controlled environment, avoiding potential breaches of compliance.

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Media and more

Integrate Local LLMs into your business today!

Getting started at Sttabot is 100% free of cost.

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