thinker-34M

Does this question need careful thinking? thinker-34M answers quick or think for a question, so an assistant can switch a model's slower "thinking" mode on only when it helps. It is Viveka-34M fine-tuned as a classifier and runs in milliseconds on a laptop CPU, next to router-34M.

Status: experimental. It is right on 68% of held-out questions (50% would be guessing), so use it only when it is very sure. In Vrishvardhan's offline assistant, thinking is switched on only when its think score is 0.85 or more.

Question	Label
hello, how are you?	quick
Why is the sky blue?	quick
What is the derivative of x squared?	think

Use

from transformers import pipeline
clf = pipeline('text-classification', model='vrishv/thinker-34M')
print(clf('What is the derivative of x squared?'))

An ONNX copy (model.onnx) is included for CPUs without PyTorch, e.g. with onnxruntime and tokenizers:

import numpy as np, onnxruntime as ort
from tokenizers import Tokenizer
from huggingface_hub import hf_hub_download
tok = Tokenizer.from_file(hf_hub_download('vrishv/thinker-34M', 'tokenizer.json'))
sess = ort.InferenceSession(hf_hub_download('vrishv/thinker-34M', 'model.onnx'))
ids = tok.encode('What is the derivative of x squared?').ids[:128]
logits = sess.run(None, {'input_ids': np.array([ids]), 'attention_mask': np.ones((1, len(ids)), dtype=np.int64)})[0]
print(['quick', 'think'][int(logits.argmax())])

Training

Fine-tuned on Kaggle (two T4 GPUs, two settings at once, the better one kept: learning rate 1e-4, 4 epochs).

Label	Examples from
quick	AI2 ARC-Easy (CC BY-SA 4.0), Jigyasa Simple (Apache 2.0), small talk from Google Synthetic-Persona-Chat (CC BY 4.0)
think	AI2 ARC-Challenge (CC BY-SA 4.0), Jigyasa Medium and Big (Apache 2.0)

Limitations

• ARC's Easy and Challenge sets are split by whether simple computer methods could answer a question, not by how the question reads, so many questions look alike. That limits how well wording alone can tell them apart. A better-labelled version is planned.
• English only. Questions are read up to 128 tokens.

About the maker

thinker-34M was built by Vrishvardhan Sharma (vrishv), a 9-year-old self-taught builder from India. His other work:

• GitaVardhan: a free, offline Bhagavad Gita app in 13 Indian languages, and a pocket-sized voice-controlled Gita device he designed, wired and coded himself.
• Sanskrit Vardhan: an app for learning Sanskrit through the Bhagavad Gita, with word-by-word meanings and step-by-step Pāṇinian derivations. Launched on 20 October 2026 by Prof. Shrinivasa Varakhedi, Vice-Chancellor of Central Sanskrit University.
• Kannada, Tamil and Telugu Vardhan: apps that teach everyday spoken Kannada, Tamil and Telugu.
• Hindi Vardhan (hindivardhan.in): a dictionary of pure, Sanskrit-rooted Hindi. Over 6,000 borrowed words in everyday Hindi, each with native alternatives checked against five classical Sanskrit dictionaries.
• AksharaVardhan: a handwriting reader that runs on an ordinary computer.
• graphics-studio: a free Space that makes and edits images, videos, music and narration.
• Viveka-34M: his small language model, trained from scratch, that this model is built on.
• Shodhana-34M: Viveka trained further to correct lines misread by a handwriting reader.
• Jigyasa Simple: 473 everyday science questions with short, plain-text answers.
• Jigyasa Medium and Jigyasa Big: 969 and 970 deeper science questions, built from his own questions, with answers of up to 7 and 10 sentences.
• router-34M: picks which of four offline models should answer a question; used next to this thinker.

He has memorised the Bhagavad Gita and Pāṇini's Aṣṭādhyāyī, won national Sanskrit recitation competitions, and speaks six languages. More at vrishvardhan.in.

CC BY-NC 4.0 © 2026 Vrishvardhan Sharma.