{"repo":"Sudharsanselvaraj/Token-Print","free":true,"listed":false,"github":"https://github.com/Sudharsanselvaraj/Token-Print","clone":"git clone https://github.com/Sudharsanselvaraj/Token-Print.git","description":"Interactive 3D visualization platform for exploring transformer architectures, tensors, and real-time LLM inference.","language":"TypeScript","stars":62,"topics":["3d","gguf-model-support","huggingface","large-language-models","llm","open-source","threejs","transformer-visualization","transformers","visualization"],"license":"MIT","category":"ai-agents","readme_excerpt":"See a language model think — real internals, real forward pass, real-time 3D. --- TokenPrint is a browser-based 3D inspector for the internals of a language model. Load a live model or drop in a .gguf file and explore its tensors, run a real greedy generation op-by-op, or walk through the transformer step by step. Every number you see is real — parsed straight from a model file or produced by an actual forward pass. Nothing is illustrative, sampled from noise, or hardcoded. [!TIP] New here? Open the Architecture tab and hit Use live Qwen model — you'll get a point cloud of the real Qwen/Qwen2.5-0.5B-Instruct tensors (494,032,768 params, 290 tensors) with hover-to-inspect names, shapes, and dtypes. Quickstart Open http://localhost:3000 and pick a mode from the top bar. No model file is required for the live-model view; drag any local .gguf onto the drop zone to inspect it instead (the file is parsed in-browser — nothing is uploaded). The four modes Mode What it shows Where the data comes from ---- ------------- ------------------------- Architecture A 3D point cloud of every real tensor (layers as depth-colored panels), a searchable tensor list with hover/click inspection, and a real-data model overview card (params, layers, attn/KV heads, hidden, FFN, vocab, context) shown until a tensor is selected. Also a 2D tile grid (tensors grouped by role, searchable), an SVG topology view , a model info pane , and a quantization compare panel that dequantizes a selected tensor from two","default_branch":null,"files":null,"tree":[],"storefront":"/r/Sudharsanselvaraj","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Sudharsanselvaraj/Token-Print/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}