tiny-random-GPTNeoXForCausalLM is a tiny randomly initialized model based on the GPT-NeoX architecture. It is used for internal testing of Optimum Intel and supports both PyTorch and ONNX formats. The model serves as a minimal example for validating model loading, inference, and export workflows.
Tiny Random GPTNeoXForCausalLM is a Foundation models & chat project. It focuses on testing compatibility and conversion pipelines for GPT-NeoX models in PyTorch and ONNX. It is built as an open-source project for developers. Tiny Random GPTNeoXForCausalLM is open source under the Open Source license. Tiny Random GPTNeoXForCausalLM is available on the web and API.
optimum-intel-internal-testing builds and maintains Tiny Random GPTNeoXForCausalLM, and it first shipped in 2025. Among its 3 catalogued features are Causal Language Modeling, Test Model, and ONNX.
Summary written by a language model from the project’s public pages.
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