Replete-Coder-Llama3-8B-GGUF

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<p style="text-align: center;">The official library of GGUF format models for use in the local AI chat app, Backyard AI.</p>

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Replete Coder Llama3 8B

• Creator: Replete-AI
• Original: Replete Coder Llama3 8B
• Date Created: 2024-06-24
• Trained Context: 8192 tokens
• Description: Replete-Coder-llama3-8b is a general purpose model that is specially trained in coding in over 100 coding languages. The data used to train the model contains 25% non-code instruction data and 75% coding instruction data totaling up to 3.9 million lines, roughly 1 billion tokens, or 7.27gb of instruct data. The data used to train this model was 100% uncensored, then fully deduplicated, before training happened.

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What is a GGUF?

GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware. GGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight.

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