Lebanese-Llama-3.1-8B is a high-performance LLM fine-tuned specifically for the Lebanese dialect (Ammiya). It bridges the gap between Modern Standard Arabic (MSA) and the multi-modal nature of Lebanese communication, seamlessly blending Arabic script, French/English influences, and Arabizi (Romanized Arabic with numbers). This model was trained and validated on the NVIDIA DGX Spark, the world’s first personal AI supercomputer powered by the Grace Blackwell (GB10) architecture. Try the model instantly in your browser without any setup: To get the most authentic "Ammiya" experience, use this system prompt. It activates the model's specialized cultural knowledge and linguistic patterns. Speak…
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mit
8B parameters
131,072 tokens
transformers
A ~10 million parameter Small Language Model (SLM) Transformer designed for binary classification to detect whether Python source code was written by a human or generated by AI. The model was trained on a dataset of human-written code extracted from GitHub (Q3 2017 and prior) and synthetic AI-generated code mimicking Q3 2026 generative AI paradigms. You can test the model interactively without writing any code by visiting our Gradio Web UI Space. To use this model locally, you must include the model architecture class in your script before loading the weights. Once the class is defined, you can automatically pull the weights from Hugging Face and run inference cleanly using this helper…
Open weights
mit