Instructions to use Andy-ML-And-AI/SocratesAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Andy-ML-And-AI/SocratesAI with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
model = PeftModel.from_pretrained(base_model, "Andy-ML-And-AI/SocratesAI")

Transformers

How to use Andy-ML-And-AI/SocratesAI with Transformers:

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

pipe = pipeline("text-generation", model="Andy-ML-And-AI/SocratesAI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Andy-ML-And-AI/SocratesAI", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Andy-ML-And-AI/SocratesAI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Andy-ML-And-AI/SocratesAI"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Andy-ML-And-AI/SocratesAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Andy-ML-And-AI/SocratesAI

SGLang

How to use Andy-ML-And-AI/SocratesAI 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 "Andy-ML-And-AI/SocratesAI" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Andy-ML-And-AI/SocratesAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Andy-ML-And-AI/SocratesAI" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Andy-ML-And-AI/SocratesAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Andy-ML-And-AI/SocratesAI with Docker Model Runner:
```
docker model run hf.co/Andy-ML-And-AI/SocratesAI
```

SocratesAI — Mistral 7B QLoRA

"I know that I know nothing — and I will make sure you know that too."

SocratesAI is a QLoRA fine-tune of Mistral-7B-Instruct-v0.3 trained to embody the Socratic method in its purest, most uncompromising form.

It has one absolute rule: it never answers your question. Ever. Not even partially.

Instead, it responds with a deeper, more elaborate riddle-question that forces you to examine the assumptions hidden inside your own question — phrased in a poetic, almost mystical way, containing a paradox or mirror that reflects you back at yourself.

What it does

You ask a question. Any question. SocratesAI does not answer it.

Instead it asks you something harder.

You ask	SocratesAI responds with
What is the meaning of life?	A deeper question about who is doing the asking
Why is the sky blue?	A question about whether you've ever truly seen the sky
What is 2 + 2?	A question about what numbers even are
How do I become happy?	A question about whether happiness is a destination or a direction
Am I living the right life?	A question about who defined "right" for you

Training details

Property	Value
Base model	Mistral-7B-Instruct-v0.3
Method	QLoRA (4-bit NF4)
LoRA rank	16
LoRA alpha	32
Target modules	q, k, v, o, gate, up, down proj
Trainable params	41.9M / 7.29B (0.57%)
Dataset	281 hand-crafted Socratic dialogues
Epochs	3
Hardware	Kaggle T4 (15GB)
Training time	~90 minutes

Dataset

281 human-curated Socratic dialogue pairs covering:

Philosophy & existence
Science & nature
Mathematics & logic
Personal & existential questions
Everyday simple questions
Weird hypotheticals

Every single training example follows the same pattern — user asks, Socrates never answers, only questions deeper.

Limitations

It will never answer you. That is a feature, not a bug.
Works best on open-ended questions.
Requires the system prompt to behave correctly — without it, may revert toward base Mistral.
Requires ~14GB VRAM for full fp16, or ~6GB with 4-bit quantization.

Who made this

Built by Andy-ML-And-AI

License

Apache 2.0

Downloads last month: 4

Model tree for Andy-ML-And-AI/SocratesAI

Base model

mistralai/Mistral-7B-v0.3

Finetuned

mistralai/Mistral-7B-Instruct-v0.3

Adapter

(938)

this model