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s3nh

s3nh
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AI & ML interests

Quantization, LLMs, Deep Learning for good. Follow me if you like my work. Patreon.com/s3nh

Recent Activity

reacted to Severian's post with 👍 about 9 hours ago
MLX port of BDH (Baby Dragon Hatchling) is up! I’ve ported the BDH ( https://github.com/pathwaycom/bdh ) model to MLX for Apple Silicon. It’s a faithful conversion of the PyTorch version: same math, same architecture (byte-level vocab, shared weights across layers, ReLU sparsity, RoPE attention with Q=K), with MLX-friendly APIs and a detailed README explaining the few API-level differences and why results are equivalent. Code, docs, and training script are ready to use. You may need to adjust the training script a bit to fit your own custom dataset. Only tested on M4 so far, but should work perfect for any M1/M2/M3 users out there. I’m currently training this MLX build on my Internal Knowledge Map (IKM) dataset https://huggingface.co/datasets/Severian/Internal-Knowledge-Map Training’s underway; expect a day or so before I publish weights. When it’s done, I’ll upload the checkpoint to Hugging Face for anyone to test. Repo: https://github.com/severian42/BDH-MLX HF model (coming soon): https://huggingface.co/Severian/BDH-MLX If you try it on your own data, feedback and PRs are welcome.
reacted to mitkox's post with 🚀 about 9 hours ago
Hermes4 70B synthetic dataset generation on my desktop Z8 GPU rig: 307 tok/sec 1.1M tok/hour The bottleneck for generating massive, high-quality reinforcement learning datasets is never the GPU compute; it's always the model's willingness to actually answer the darn question.
liked a model about 12 hours ago
Jackmin108/glm-0.5B
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