WFGY/examples/example_04_remote_inference.py
2025-06-15 13:15:13 +08:00

61 lines
3.2 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

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