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⚡ https://web.tribute.tg/d/KIH ⚡ If you like this Genesis LLM release you can donate to me via @Tribute bot in Telegram messenger and support future Genesis LLM development.
⚡ Generate an SVG of a pelican riding a bicycle. ⚡ Result: pelican.svg
⚡ Why Genesis project exists? During training, ALL models don't just learn knowledge - they also accumulate random noise in their tensors. This noise builds up and creates something I call the Noise Gate - a fundamental barrier that stops LLM models from learning further and makes them unstable, verbose, and prone to hallucinations. My approach reduces this noise. It repairs the signal without touching the learned knowledge and gradient. The result is a model that consistent in performance, context clarity and following instructions, because it's no longer fighting its own internal chaos.
What is Genesis? Genesis is post training data regeneration and calibrarion algorythm for neural networks (LLM) in GGUF format that I made with AI help during almost half a year of development. It's optimized, architecture independent, works with any model in GGUF format and based on mathematical statistics. I don't train or finetune models, I repair purity of signal in them instead on Google Collab Free on Tesla T4 GPU via Python based on how models learns information. On first stage I scan ssm_conv1d tensors in model, they handle long context memory. I repair balance between heads in them. On second stage I scan model and detect noise in tensors via custom SVD. During scanning I exclude token_embd.weight, output.weight, ffn_gate_inp_shexp.weight, 1D tensors, bias and norms. Then I reduce training noise in tensors via custom SVD with preserved training data, 99% of siginal and learned gradient. On third stage, I scan blocks in model via chunks via 3 parameters and pick best one that fits to weight distribution in tensor. Best picked chunk replaces zero chunks in broken tensor without touching learned structure in model
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You are Qwen, a large language model created by Tongyi Lab team from Alibaba Group. You are a helpful assistant.You are a helpful assistant.agent identity: linkassistant identity: System_Prompt_Creative.txttemperature=0.6, top_p=0.95, top_k=20, min_p=0, seed=42, presence_penalty=disabled, repeat_penalty=disabledtemperature=1.0, top_p=0.95, top_k=20, min_p=0.05, seed=42, presence_penalty=disabled, repeat_penalty=disabledtemperature=1.0, top_p=0.85, top_k=20, min_p=0.015, seed=42, presence_penalty=disabled, repeat_penalty=disabledYou are Qwen, a large language model created by Tongyi Lab team from Alibaba Group. You are a helpful assistant that answers in JSON. Here's the json schema you must adhere to:\n<schema>\n{schema}\n</schema>.V5 version of this model is useful for uncensored local roleplay. For coding 27B Genesis is a lot better.
You are Qwen, a large language model created by Tongyi Lab team from Alibaba Group. You are a helpful assistant.temperature=0.6, top_p=0.95, top_k=20, min_p=0, seed=42, presence_penalty=disabled, repeat_penalty=disabledHello. What is your name?Generate an SVG of a pelican riding a bicycle.--jinja flag with llama.cpp for proper chat template handlingmmproj file alongside the main GGUF