Instructions to use 11-47/GPT2.5.5-Awakened.Thinker-0.1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 11-47/GPT2.5.5-Awakened.Thinker-0.1B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="11-47/GPT2.5.5-Awakened.Thinker-0.1B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("11-47/GPT2.5.5-Awakened.Thinker-0.1B")
model = AutoModelForMultimodalLM.from_pretrained("11-47/GPT2.5.5-Awakened.Thinker-0.1B")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use 11-47/GPT2.5.5-Awakened.Thinker-0.1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "11-47/GPT2.5.5-Awakened.Thinker-0.1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "11-47/GPT2.5.5-Awakened.Thinker-0.1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/11-47/GPT2.5.5-Awakened.Thinker-0.1B

SGLang

How to use 11-47/GPT2.5.5-Awakened.Thinker-0.1B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "11-47/GPT2.5.5-Awakened.Thinker-0.1B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "11-47/GPT2.5.5-Awakened.Thinker-0.1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "11-47/GPT2.5.5-Awakened.Thinker-0.1B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "11-47/GPT2.5.5-Awakened.Thinker-0.1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use 11-47/GPT2.5.5-Awakened.Thinker-0.1B with Docker Model Runner:
```
docker model run hf.co/11-47/GPT2.5.5-Awakened.Thinker-0.1B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

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GPT2.5.5-Awakened.Thinker-0.1B

Forged by WithIn Us AI — a fully fine-tuned GPT-2 awakened on distilled GPT-5.5 thinking patterns.

Model Overview

Property	Value
Architecture	GPT-2 (`openai-community/gpt2`)
Parameters	~124M (0.1B class)
Training Type	Full fine-tune — ALL weights updated, zero adapters
Context Window	1024 tokens
Best Eval Loss	`0.4365`
Best Perplexity	`1.55`
Creator	GODsStrongestSoldier / WithIn Us AI
Date Trained	2026-05-23
Hardware	2× NVIDIA Tesla T4 (Kaggle)
Precision	FP16 mixed precision

Training Methodology

Full fine-tuning — every single parameter in GPT-2 was updated. No LoRA, no QLoRA, no adapters of any kind.

Datasets

Dataset	Description
`WithinUsAI/GPT_5.5_Distilled`	Instruction + completion pairs distilled from GPT-5.5
`WithinUsAI/GPT5.5_thinking_max_distill_god_seed_25K`	25K chain-of-thought reasoning traces distilled from GPT-5.5

97 / 3 train / eval split.

Hyperparameters

Parameter	Value
Peak Learning Rate	`3e-5`
LR Schedule	Cosine with 6% warmup
Effective Batch Size	`64` (4 × 2 GPUs × 8 grad accum)
Epochs	`5`
Weight Decay	`0.1`
Max Sequence Length	`1024`
Precision	FP16

Quick Start

from transformers import GPT2LMHeadModel, GPT2TokenizerFast
import torch

model_id  = "GODsStrongestSoldier/GPT2.5.5-Awakened.Thinker-0.1B"
tokenizer = GPT2TokenizerFast.from_pretrained(model_id)
model     = GPT2LMHeadModel.from_pretrained(model_id, torch_dtype=torch.float16)
model.eval()

prompt = "Let me think through this carefully, step by step:"
inputs = tokenizer(prompt, return_tensors="pt")

with torch.no_grad():
    output = model.generate(
        **inputs,
        max_new_tokens     = 200,
        do_sample          = True,
        temperature        = 0.7,
        top_p              = 0.9,
        repetition_penalty = 1.15,
    )

print(tokenizer.decode(output[0], skip_special_tokens=True))

About WithIn Us AI

HuggingFace org : WithinUsAI
Creator : GODsStrongestSoldier

"Strength through understanding. Awakened from within."

Downloads last month: 206

Safetensors

Model size

0.1B params

Tensor type

F32

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GPT2.5.5-Awakened.Thinker-0.1B