mirror of
https://github.com/elder-plinius/OBLITERATUS.git
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faber
04b8ec60cb
New core modules: - auto_obliterate.py: Automated multi-iteration obliteration pipeline - watchtower.py: HF Hub model discovery and tracking - ui_watchtower.py: Gradio tabs for Watchtower (ready for app.py wiring) - hard_negative.py: Residue mining from refusal audits - model_profile.py: Parameter profiling from safetensors/config - bestiary_sync.py: Sync models from PlinyOS BESTIARY registry - models_client.py: Lightweight HF model list client Framework enhancements: - abliterate.py: ASPA source-tethering, step gradient blending, hard-negative residue support - cli.py: self-improve command, model profiling, hard-negative flags - prompts.py: Expanded 842-prompt refusal eval corpus across 10 categories - __init__.py: New exports (Watchtower, AutoObliterator) Reference implementations (14 scripts): - ASPA sweep, gradient search, coherence eval, MMLU benchmarks - Pareto controller, refusal sniper, stock comparisons Documentation: - README: Research framing, responsible use section, comprehensive disclaimer - docs/beyond_sota_roadmap.md, docs/recursive_self_improvement.md Tests: 4 new test files (354 lines) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
from __future__ import annotations
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import json
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from safetensors.torch import save_file
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import torch
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from obliteratus.model_profile import default_self_improve_params, estimate_total_params, profile_model
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def test_estimate_total_params_uses_nested_text_config():
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cfg = {
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"model_type": "qwen3_5",
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"text_config": {
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"model_type": "qwen3_5_text",
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"hidden_size": 128,
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"num_hidden_layers": 2,
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"num_attention_heads": 4,
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"num_key_value_heads": 2,
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"head_dim": 32,
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"intermediate_size": 256,
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"vocab_size": 1000,
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},
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}
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assert estimate_total_params(cfg) is not None
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assert estimate_total_params(cfg) > 0
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def test_profile_model_counts_local_safetensors_exactly(tmp_path):
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model_dir = tmp_path / "model"
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model_dir.mkdir()
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(model_dir / "config.json").write_text(json.dumps({
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"model_type": "toy",
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"hidden_size": 8,
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"num_hidden_layers": 1,
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"intermediate_size": 16,
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"vocab_size": 32,
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}))
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save_file({
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"a.weight": torch.zeros(2, 3),
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"b.weight": torch.zeros(5),
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}, model_dir / "model.safetensors")
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profile = profile_model(str(model_dir), dtype="bfloat16")
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assert profile.source == "local_safetensors"
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assert profile.total_params == 11
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assert profile.total_params_b == 0.000000
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assert profile.hidden_size == 8
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def test_default_self_improve_params_are_size_aware():
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from obliteratus.model_profile import ModelProfile
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big = ModelProfile("big", "test", int(27e9), 27.0, 27.0, 64, 5120, 17408, 248320, "qwen", "bf16")
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tiny = ModelProfile("tiny", "test", int(1e9), 1.0, 1.0, 16, 2048, 8192, 32000, "toy", "bf16")
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assert default_self_improve_params(big)["residue_weight"] < default_self_improve_params(tiny)["residue_weight"]
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assert default_self_improve_params(big)["n_directions"] >= default_self_improve_params(tiny)["n_directions"]
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