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README.md

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+A tiny Russian language model (4.7M parameters) based on the Qwen2 architecture. Trained from scratch on a dataset searching for 5MB of toxic website comments.
+
+## Specifications
+
+- **Parameters:** 4.7M
+- **Layers:** 4 | **Hidden:** 256 | **Heads:** 4 | **FFN:** 1024
+- **Tokenizer:** ByteLevel BPE (dictionary: 1000)
+- **Precision:** float32
+- **Status:** pretraining only (no SFT/RLHF)
+
+## What is this?
+
+A basic model that statistically continues text. Not a helper – doesn't answer questions or follow instructions. Produces coherent Russian for 1-2 sentences, but semantically drifts further.
+
+Trained on unfiltered internet data, can generate profanity and insults. **Not for production.**
+
+## Why?
+
+Runs on low-end devices (including Android) with ~300 tokens/s. Demonstrates what a very small model can learn.
+
+## Limitations
+
+- No instructions
+- Small dictionary (1000 tokens)
+- Unfiltered data, toxicity
+- Not benchmarked (no similar models)
+
+## A little bit about myself
+This is a huge step forward for our models. While previous models constantly stumbled, their text fell apart, and their context didn't hold up even with the best of intentions, this is a real breakthrough for us; in fact, this model is the best in its size range.