Fork of Text Generation Inference.

We use essential cookies to make our site work. With your consent, we may also use non-essential cookies to improve user experience and analyze website traffic…

DeepInfra raises $107M Series B to scale the inference cloud — read the announcement

Published on 2023.08.09 by Nikola Borisov

The text generation inference open source project by huggingface looked like a promising framework for serving large language models (LLM). However, huggingface announced that they will change the license of code with version v1.0.0. While the previous license Apache 2.0 was permissive, the new one is restrictive for our use cases.

Forking the project

We decided to fork the project and continue to maintain it under the Apache 2.0 license. We will continue to contribute to the project and keep it up to date. We will accept pull requests from the community, and we will keep the project truly open source and free to use.

Here is a link to the code: https://github.com/deepinfra/text-generation-inference

We hope that in time a community of other developers and organizations that want to keep this project truly open source will form around it.

License changes mid-flight

Sadly it is becoming more and more common for popular open source projects to change their license after they gain some traction. This happened with MongoDB, Grafana, ElasticSearch, and many others. As a developer, when you decide to adopt a particular open source project, you start investing time and effort into using it. You build your application around it, and you start depending on it. Then, suddenly, the license changes, and you might be forced to find an alternative.

Imagine if meta changes the license of pytorch. Or if tomorrow huggingface decides to change the license of transformers in a similar way to prohibit commercial use.

We believe that the changing of the license of open source projects mid-flight is a unfriendly move towards the community.

If you need any help, just reach out to us on our Discord server.

OpenClaw Cost Optimization: Cut AI API Costs by 90%A single ask in an OpenClaw session can cost more than a full evening of casual ChatGPT use. Ask your agent something simple, like which calendar event clashes with your flight, and the request that hits the API carries far more than your 12-token question. It also carries your SOUL.md, the tool schemas registered on […]

LLM API Provider Performance KPIs 101: TTFT, Throughput & End-to-End GoalsFast, predictable responses turn a clever demo into a dependable product. If you’re building on an LLM API provider like DeepInfra, three performance ideas will carry you surprisingly far: time-to-first-token (TTFT), throughput, and an explicit end-to-end (E2E) goal that blends speed, reliability, and cost into something users actually feel. This beginner-friendly guide explains each KPI […]

GLM-5 API Benchmarks: Latency, Throughput & CostGLM-5 is the latest open-weights reasoning model released by Z AI (Zhipu AI) in February 2026, characterized by high “thinking token” usage. It is a Mixture of Experts (MoE) model with 744B total parameters and 40B active parameters, scaling up from GLM-4.5’s 355B parameters. The model was pre-trained on 28.5T tokens and features a 200K+ […]

View all