Cass-Beta1.3

Cass-Beta1.3: From-Scratch Meme-Teen AI Transformer

Cass-Beta1.3 is a fully-from-scratch Transformer language model with a PG-13 meme-teen personality. It does not use any pretrained weights—all knowledge comes from auto-generated personality prompts and adaptive learning from user interactions.

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Model Overview

• Architecture: GPT-2 style Transformer (GPT2LMHeadModel)
• Parameters: Small and lightweight (~1 million parameters) suitable for 12 GB GPU
• Tokenizer: Custom BPE tokenizer trained from scratch
• Training Data:
  • 100 auto-generated personality prompts (PG-13, meme-teen)
  • Incrementally updated with user chat memory for adaptive learning
• Personality: Funny, chill, slang-heavy, PG-13
• Memory Learning: Model fine-tunes itself every 10 user messages, adapting to user style

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Intended Use

• Personal chatbot with a meme-teen style
• Text generation for PG-13 contexts
• Educational/demo purposes for small-scale Transformer training

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Limitations

• Small parameter count → limited reasoning capability
• Slang-heavy personality may produce nonsensical or repetitive output
• Memory learning is local to user interactions; may overfit short-term style
• Lookup functionality is simulated; no live web access

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Files Included

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Usage Example

from transformers import GPT2LMHeadModel, PreTrainedTokenizerFast

# Load model
model = GPT2LMHeadModel.from_pretrained("DSDUDEd/Cass-Beta1.3")
tokenizer = PreTrainedTokenizerFast.from_pretrained("DSDUDEd/Cass-Beta1.3")

# Encode user input
input_text = "yo cass, what's up?"
inputs = tokenizer(input_text, return_tensors="pt")

# Generate reply
outputs = model.generate(**inputs, max_length=32, do_sample=True, temperature=0.8)
reply = tokenizer.decode(outputs[0])

print("Cass:", reply)