| { | |
| "module_name": "compot_compressor", | |
| "class_name": "COMPOTCompressor", | |
| "category": "compression", | |
| "family": "compression", | |
| "params": [ | |
| "in_features", | |
| "out_features", | |
| "rank", | |
| "bias", | |
| "dtype", | |
| "device", | |
| "model", | |
| "calibration_texts", | |
| "tokenizer", | |
| "cfg", | |
| "target_layers" | |
| ], | |
| "ops": [ | |
| "reshape", | |
| "linear", | |
| "view" | |
| ], | |
| "docstring": "COMPOT (Compressed Orthogonal Dictionary Learning) Compressor.\nLearns a low-rank basis from activation QR decompositions and compresses\nlinear layers into factorized COMPOTLinear modules.\n\nArgs:\n model: PyTorch model.\n rank: Target rank for factorization.\n calibration_texts: Optional calibration texts.\n tokenizer: Optional tokenizer.\n cfg: Optional configuration object.\n target_layers: Optional target layer filter.", | |
| "rank": 32, | |
| "d_state": 1, | |
| "num_experts": 1, | |
| "top_k": 1, | |
| "sparsity_pct": 0.0, | |
| "bits": 4, | |
| "hash_val": 180748376431327030690668207549126466182 | |
| } |
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