Supra-50M-Reasoning: Open-Source Tiny Model with Chain-of-Thought Thinking

SupraLabs released Supra-50M-Reasoning (ThinkSupra-50M), a tiny 50M-parameter model that produces a full chain-of-thought (CoT) before responding. It's the reasoning variant of Supra-50M-Instruct, fine-tuned from Supra-50M-Base using a synthetic dataset of 500 examples generated by Qwen3 1.7B, trained for 6 epochs with SFT in bfloat16. Experimental, prone to hallucination, and fully open.

Inference Format

Every response follows this structure:

<|begin_of_thought|> ... thinking ... <|end_of_thought|> <|begin_of_solution|> ... final answer ... <|end_of_solution|>

Quick Start

import torch
from transformers import pipeline, AutoTokenizer

MODEL_ID = "SupraLabs/Supra-50M-Reasoning"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, clean_up_tokenization_spaces=False)
pipe = pipeline("text-generation", model=MODEL_ID, tokenizer=tokenizer, device_map="auto", torch_dtype=torch.bfloat16 if torch.cuda.is_available() else torch.float32)
def build_prompt(instruction, input_text=""):
    if input_text.strip():
        return f"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Input:\n{input_text}\n\n### Response:\n"
    return f"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n"
def generate(instruction, input_text=""):
    result = pipe(build_prompt(instruction, input_text), max_new_tokens=512, do_sample=True, temperature=0.3, top_k=50, top_p=0.9, repetition_penalty=1.15, pad_token_id=pipe.tokenizer.pad_token_id, eos_token_id=pipe.tokenizer.eos_token_id, return_full_text=False)
    return result[0]['generated_text'].strip()

Sample Output

Prompt: "What is AI?"

Thinking: "Okay, the user is asking about AI. Let me start by recalling what AI is. AI is a subset of machine learning, specifically neural networks..."

Response: "AI is a subset of machine learning that focuses on enabling machines to learn from data... used in healthcare, finance and even in the field of robotics."

What's Next

SupraLabs plans larger models: Supra-124M (Base, Chat, Reasoning) and Supra-350M (Base, Chat, Reasoning, Coding).

Model on Hugging Face: Supra-50M-Reasoning
Dataset: SupraThink-Dataset-500x