README.md

---
base_model:
- gss1147/GPT2.5.2-high-reasoning-codex-0.4B
- openai-community/gpt2-medium
model-index:
- name: gpt2-finetuned
  results: []
datasets:
- TeichAI/gpt-5.1-codex-max-1000x
- TeichAI/gpt-5.2-high-reasoning-250x
- jjmachan/NSFW-reddit
- gss1147/GPT-2-to-GPT-5-5k
- TeichAI/gpt-5-codex-250x
- TeichAI/gpt-5.1-high-reasoning-1000x
---
GPT2.5.2-NSFW-Codex-0.4B

📌 Model Overview

Model Name: WithinUsAI/GPT2.5.2-NSFW-Codex-0.4B
Organization: Within Us AI
Base Model: openai-community/gpt2-medium (~0.4B parameters)  
Model Type: Instruction-Tuned Code + General Text LLM
Parameter Size: ~0.4B
Primary Focus: Lightweight coding + uncensored responses + dataset-driven evolution

This model represents a heavily evolved GPT-2 Medium, upgraded through dataset-driven training and reasoning/coding distillation.

🧬 Name Meaning

“GPT2.5.2” = Evolution lineage

* 2 → GPT-2 Medium base
* .5.2 → GPT 5.2 Codex-style 

👉 In short:
A GPT-2 model pushed forward toward modern coding + reasoning behavior using curated datasets, not architecture scaling.

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🧬 Architecture & Lineage

Base Foundation

* Transformer architecture from GPT-2 Medium (~345M–400M parameters class)  
* Dense, autoregressive language model

Evolution Process

This model was scaled up,evolved through data and training strategy:

* Instruction tuning
* Coding dataset exposure (Codex-style tasks)
* Reasoning trace influence
* Behavioral refinement toward modern LLM outputs

⸻

🧠 Core Design Philosophy

Don’t scale the model… evolve it.

Instead of increasing parameters, this model:

* Improves behavior through data quality
* Mimics GPT 5.2 Codex reasoning styles
* Pushes GPT-2 into modern task domains

Think of it like a classic engine rebuilt with modern parts 🔧

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⚙️ Key Capabilities

💻 Coding (Codex-Inspired)

* Basic code generation (Python, JS, etc.)
* Simple debugging assistance
* Structured function outputs

🧠 Reasoning (Lightweight)

* Step-by-step responses (limited depth)
* Instruction-following improvements over base GPT-2

🔓 Uncensored Behavior

* Reduced refusal tendencies
* More permissive outputs compared to aligned models

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📦 Model Characteristics

Attribute	Value
Parameters	~0.4B
Architecture	GPT-2 (dense transformer)
Strength	Efficiency
Weakness	Limited deep reasoning

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🚀 Intended Use

✅ Ideal Use Cases

* Ultra-lightweight local LLMs
* Experimental coding assistants
* Dataset-driven model research
* Uncensored response exploration
* Edge/low-resource environments

⚠️ Limitations

* Significantly weaker than modern 7B+ models
* Limited context and reasoning depth

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🛠️ Example Usage (Transformers)

from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "WithinUsAI/GPT2.5.2-NSFW-Codex-0.4B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
prompt = "Write a Python function to reverse a string."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))

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🧪 Training Methodology

Within Us AI approach:

* Dataset-driven evolution (primary driver)
* Instruction + coding task fine-tuning
* Reasoning-style output shaping

Data Sources

* Proprietary datasets created by Within Us AI
* Third-party datasets used without ownership claims
* Likely includes:
    * Coding tasks
    * Instruction datasets
    * Reasoning traces

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📊 Expected Performance Profile

Capability	Strength
Efficiency	Very High
Coding (basic)	High
Reasoning	High
Creativity	Moderate
Safety filtering	Minimal

⸻

📜 License

License Type: Based on GPT-2 (OpenAI open model lineage)**

Attribution Notes:

* Base model: OpenAI GPT-2 Medium
* Training / evolution: Within Us AI
* Third-party datasets used without ownership claims
* Credit belongs to original dataset and model creators

⸻

🙏 Acknowledgements

* OpenAI (GPT-2 architecture)
* Hugging Face (model hosting ecosystem)
* Open-source dataset contributors
* Coding dataset communities

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🔗 Links

* Model: https://huggingface.co/WithinUsAI/GPT2.5.2-NSFW-Codex-0.4B
* Organization: https://huggingface.co/WithinUsAI

⸻

🧩 Closing Note

This model is like a time traveler from 2019 carrying tools from 2026 ⏳⚡

Same small brain…
but trained to think like GPT 5.2 Codex.