| --- |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| library_name: transformers |
| pipeline_tag: text-classification |
| base_model: vrishv/Viveka-34M |
| tags: |
| - text-classification |
| - reasoning-detection |
| - small-model |
| - tiny-model |
| - llama |
| - onnx |
| - english |
| - 34m |
| datasets: |
| - allenai/ai2_arc |
| - google/Synthetic-Persona-Chat |
| - vrishv/jigyasa-simple |
| - vrishv/jigyasa-medium |
| - vrishv/jigyasa-big |
| --- |
| |
| # 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](https://huggingface.co/vrishv/Viveka-34M) |
| fine-tuned as a classifier and runs in milliseconds on a laptop CPU, next to [router-34M](https://huggingface.co/vrishv/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 |
|
|
| ```python |
| 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`: |
|
|
| ```python |
| 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](https://huggingface.co/datasets/vrishv/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](https://huggingface.co/datasets/vrishv/jigyasa-medium) and [Big](https://huggingface.co/datasets/vrishv/jigyasa-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](https://huggingface.co/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](https://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](https://huggingface.co/spaces/vrishv/graphics-studio)**: a free Space that makes and edits images, videos, music and narration. |
| - **[Viveka-34M](https://huggingface.co/vrishv/Viveka-34M)**: his small language model, trained from scratch, that this model is built on. |
| - **[Shodhana-34M](https://huggingface.co/vrishv/Shodhana-34M)**: Viveka trained further to correct lines misread |
| by a handwriting reader. |
| - **[Jigyasa Simple](https://huggingface.co/datasets/vrishv/jigyasa-simple)**: 473 everyday science questions with |
| short, plain-text answers. |
| - **[Jigyasa Medium](https://huggingface.co/datasets/vrishv/jigyasa-medium)** and **[Jigyasa Big](https://huggingface.co/datasets/vrishv/jigyasa-big)**: |
| 969 and 970 deeper science questions, built from his own questions, with answers of up to 7 and 10 sentences. |
| - **[router-34M](https://huggingface.co/vrishv/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](https://vrishvardhan.in). |
|
|
| CC BY-NC 4.0 © 2026 Vrishvardhan Sharma. |
|
|
