---
license: mit
language:
- ru
- en
pipeline_tag: text-generation
tags:
- eblan
model-index:
- name: eblan-2.0-flash-lite
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Synthetic Benchmark
      type: synthetic
    metrics:
    - name: Accuracy
      type: accuracy
      value: 314
---

# 🚀 Eblan 2.0 Flash Lite (`EblanForCausalLM`)

**Eblan 2.0 Flash Lite** is a next-generation lightweight language model built on the custom `EblanForCausalLM` architecture.

By leveraging an innovative **O(1)** polynomial recurrent state kernel, the model delivers ultra-fast inference with virtually zero memory overhead, running natively via NumPy and Tiktoken.

---

## 🏗️ Architecture (`EblanForCausalLM`)

Unlike traditional Transformer-based models that rely on heavy Attention blocks (**Q**, **K**, **V**), `EblanForCausalLM` utilizes a single scalar weight vector **W** (in **R**¹) with a direct scalar projection layer.

### Forward Pass Formulation:

$$y = W \cdot (x^2 + x) \cdot \text{vocab\_size}$$

Where:

* **x** = `current_id` / `vocab_size` — normalized input token index.
* **W** — trained scalar weight (`eblan-2.0-flash-lite.npy`).
* **Logits** formula for distance-based logit calculation prior to Softmax sampling:

$$\text{Logits}_i = -\frac{|i - y|}{\tau}$$

---

## 📜 License

This project is licensed under the **MIT License**.