Sutra-Instruct-v2-350M
is a highly optimized, 350-million parameter language model built for developers and researchers. It has undergone rigorous
Continuous Pre-Training (CPT)
to dramatically improve its logical reasoning, mathematical deduction, and Python coding capabilities.
Despite its lightweight footprint, Sutra-Instruct-v2 acts as a highly capable "Witty Coder" and educational assistant, punching well above its weight class thanks to a carefully curated, high-IQ dataset recipe.
To transition the model from a general-purpose base to a reasoning and bit of coding , we executed a Continuous Pre-Training phase using approximately
3.3 Billion high-quality tokens
.
The dataset mixture was meticulously balanced to prevent overfitting while maximizing logical deduction:
Dataset
Source
Focus
Target Tokens
The Stack Dedup
bigcode/the-stack-dedup
Pure Python Code (
content
)
1.5 Billion
DCLM-Edu
HuggingFaceTB/dclm-edu
High-IQ Educational Web Data
600 Million
Cosmopedia (Stanford)
HuggingFaceTB/cosmopedia
Synthetic Textbooks
500 Million
Tiny-Codes-QA
nampdn-ai/tiny-codes
Prompt/Response Coding Tasks
500 Million
Tiny-Textbooks
nampdn-ai/tiny-textbooks
General Knowledge / STEM
100 Million
MetaMathQA
meta-math/MetaMathQA
Mathematical Reasoning
100 Million
🛠️ Intended Use Cases
Lightweight Code Copilot:
Generating Python scripts, debugging syntax, and writing algorithms locally on low-VRAM hardware.
Edge Devices:
Perfect for deployment on Raspberry Pi, older laptops, or mobile devices where massive LLMs cannot run.
Educational QA:
Answering STEM, logic, and general knowledge questions.
Runs of Abiray Sutra-Instruct-v2-350M on huggingface.co
20
Total runs
0
24-hour runs
1
3-day runs
3
7-day runs
13
30-day runs
More Information About Sutra-Instruct-v2-350M huggingface.co Model
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