Text Generation
PEFT
Safetensors
Transformers
lora
qlora
sft
trl
philosophy
socratic-method
conversational
Instructions to use Andy-ML-And-AI/SocratesAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
| base_model: mistralai/Mistral-7B-Instruct-v0.3 | |
| library_name: peft | |
| model_name: SocratesAI | |
| tags: | |
| - base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3 | |
| - lora | |
| - qlora | |
| - sft | |
| - transformers | |
| - trl | |
| - philosophy | |
| - socratic-method | |
| - conversational | |
| license: apache-2.0 | |
| pipeline_tag: text-generation | |
| # 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 |