tiny-Lfm2ForCausalLM is a very small causal language model created by the TRL (Transformers Reinforcement Learning) internal testing team. It serves as a minimal test fixture for validating training, fine-tuning, and alignment pipelines within the Hugging Face TRL library. The model includes a chat template and tokenizer configuration suitable for rapid iteration during library development and CI testing.
Tiny Lfm2ForCausalLM is a Foundation models & chat project. It focuses on providing a minimal reproducible model for testing and validating reinforcement learning and alignment code in the TRL library. Tiny Lfm2ForCausalLM is an open-source project aimed at developers. Tiny Lfm2ForCausalLM is open source under the Apache-2.0 license. Tiny Lfm2ForCausalLM is available on the web and the command line, and it can be self-hosted.
It is developed by trl-internal-testing, and it first shipped in 2020. The project is developed in the open on GitHub with 19k stars and 556 commits in the last 90 days. It operates in a well-populated space: PulseGate tracks 18 similar projects. Among its 4 catalogued features are Causal Language Model, Test Model, and Tiny Architecture. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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