Download codebook/config.json from chuchuxwx/GenMem: direct link, hf CLI and curl.
- Browser
- Download file 1.03 kB
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https://huggingface.co/chuchuxwx/GenMem/resolve/main/codebook/config.json
- Command line
-
hf download hf://chuchuxwx/GenMem/codebook/config.json
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curl -L -o config.json https://huggingface.co/chuchuxwx/GenMem/resolve/main/codebook/config.json
1.03 kB
| { | |
| "codebook_sizes": [48, 16, 8, 8], | |
| "embedding_dim": 1024, | |
| "spherical_weight_per_level": [0.5, 0.5, 0.5, 0.5], | |
| "distance": "(1-w)*squared_euclidean + w*(1-cosine)", | |
| "residual_update": "residual - selected_center; no per-level renormalization", | |
| "embedding": { | |
| "model": "Qwen/Qwen3-Embedding-0.6B", | |
| "revision": "97b0c614be4d77ee51c0cef4e5f07c00f9eb65b3", | |
| "instruction": "Instruct: Encode the following agent experience as a reusable problem-solving memory for semantic retrieval and SID clustering. Focus on the problem type, reusable skill, preconditions, procedure, decision rules, verification checks, outcome, and failure recovery. Prefer semantic problem-solving patterns over dataset names, run ids, wording artifacts, or incidental entities unless they are essential to the skill.\nQuery: ", | |
| "max_length": 8192, | |
| "pooling": "last EOS if present, otherwise last token; one text per forward pass", | |
| "normalization": "L2 before quantization", | |
| "dtype": "float16 on CUDA; float32 on CPU" | |
| } | |
| } | |