Beta

Explore
Marketplace
Neural Labs
Playground
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

prefix-einstein – AI Model by debaterhub | AlphaNeural AI

You can deploy this model and start earning money today!

debaterhub/
prefix-einstein

like

0

text-generation

Qwen/Qwen3-30B-A3B

Views

No views yet

Einstein Prefix Adapter

Prefix-tuned adapter that teaches the model to embody Albert Einstein's reasoning patterns, voice, and philosophical positions.

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-30B-A3B")
model = PeftModel.from_pretrained(base_model, "debaterhub/prefix-einstein")

tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-30B-A3B")

Training Details

Method: PEFT Prefix-Tuning (40 virtual tokens)
Base Model: Qwen/Qwen3-30B-A3B (30B MoE, 3B active)
Dataset: 447 examples of Einstein-style debate responses
Epochs: 3
Hardware: 8x A100-40GB

Evaluation

Evaluated using LLM-as-Judge (Claude Opus 4.5) on 5 dimensions:

Ideational Fidelity (35%)
Reasoning Pattern (25%)
Voice Authenticity (20%)
Engagement Quality (15%)
Anti-Patterns (5%)

Baseline: 3.3/5.0 Trained: 3.4/5.0

Key improvement: Reduced meta-roleplay anti-patterns, more direct in-character responses.

Framework Versions

PEFT 0.18.0
Transformers 4.46.0