This is a minimal random-weight model based on the LlamaForCausalLM architecture, published on Hugging Face. It is intended for testing and development purposes, allowing developers to validate pipelines, tokenizers, and inference code without downloading full-scale models. It supports the Transformers library and can be used locally or via the Hugging Face inference ecosystem.
Tiny Random LlamaForCausalLM is a Foundation models & chat project. It focuses on needing a minimal random model for testing and debugging LlamaForCausalLM implementations without large compute requirements. It is built as an open-source project for machine learning developers. Tiny Random LlamaForCausalLM is open source under the Open Source license. It runs on the web, the command line, and API.
Behind Tiny Random LlamaForCausalLM is Hugging Face, based in the United States, and it first shipped in 2023. Among its 3 catalogued features are Causal Language Modeling, Test Model, and Transformers Compatible.
Summary written by a language model from the project’s public pages.
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