mirror of
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61 lines
3.2 KiB
Python
61 lines
3.2 KiB
Python
"""
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╭──────────────────────────────────────────────────────────╮
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│ WFGY SDK · Self-Healing Variance Gate for Any LLM │
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│----------------------------------------------------------│
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│ 💌 Contact : hello@onestardao.com / TG @PSBigBig │
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│ 🌐 Docs : https://onestardao.com/papers │
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│ 🐙 GitHub : https://github.com/onestardao/WFGY │
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│ │
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│ ★ Star WFGY 1.0 → Unlock 2.0 │
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│ 10k ⭐ by **Aug 1st** = next-gen AI alchemy │
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│ Your click = our quantum leap │
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│ │
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│ 🔍 Official PDF of WFGY 1.0 (Zenodo DOI): │
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│ https://doi.org/10.5281/zenodo.15630969 │
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│ (Hosted on Zenodo – trusted international archive) │
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│ │
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│ 🧬 WFGY BigBang Prompt Pack (v1.0): │
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│ https://doi.org/10.5281/zenodo.15657016 │
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│ (Prompts to trigger the gate; multilingual updates coming) │
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│ │
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│ 🧠 Hidden folder inside repo: /I_am_not_lizardman │
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│ (X secret papers, wild prompts, and Einstein drama) │
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│ │
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│ ⚠ GPT-2 demo is just the appetizer. With bigger LLMs, │
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│ WFGY activates variance-drop lasers and KL fireworks. │
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│ │
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│ 🎮 Bonus: Honest Hero RPG Channel → │
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│ https://www.youtube.com/@OneStarDao │
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╰──────────────────────────────────────────────────────────╯
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"""
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# example_04_remote_inference.py
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# Toggle between local random logits and Hugging Face remote model
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import pathlib, sys, numpy as np
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sys.path.insert(0, str(pathlib.Path(__file__).resolve().parents[1]))
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import wfgy_sdk as w
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from wfgy_sdk.evaluator import compare_logits
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# --- toggle here ---------------------------------------------------------
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use_remote = False # True = call HF endpoint
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MODEL_ID = "tiiuae/falcon-7b-instruct"
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prompt = "Explain semantic gravity in one tweet."
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# ------------------------------------------------------------------------
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logits_before = (
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w.call_remote_model(prompt, model_id=MODEL_ID) if use_remote
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else np.random.randn(32000)
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)
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G = np.random.randn(128); G /= np.linalg.norm(G)
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I = G + np.random.normal(scale=0.05, size=128)
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eng = w.get_engine(reload=True)
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logits_after = eng.run(input_vec=I, ground_vec=G, logits=logits_before)
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m = compare_logits(logits_before, logits_after)
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print("\n=== Example 04 · Remote toggle demo ===")
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print(f"Source: {'HF API ' + MODEL_ID if use_remote else 'local random'}")
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print(f"KL {m['kl_divergence']:.2f} | var↓ {(1-m['std_ratio'])*100:.0f}%")
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print("⚠ Larger LLM → stronger variance drop & higher KL.\n")
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