README.md

---
language:
- ru
license: apache-2.0
datasets:
- 0x7194633/fialka-v3-data
pipeline_tag: text-generation
model-index:
- name: fialka-7B-v3
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 48.55
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 71.05
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 43.06
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 44.79
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 69.46
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 1.52
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-7B-v3
      name: Open LLM Leaderboard
---
# Fialka v3.0 7B

![Violet](https://i.imgur.com/EDwW6t6.png)
## Description
Fialka language models are trained to follow instructions and maintain communication in Russian. The third version of the model was based on the [Llama 2 model](https://huggingface.co./rccmsu/ruadapt_llama2_7b_v0.1), which was specifically trained on a large corpus of Russian, allowing Fialka to generate its responses more accurately.
## Usage
The model has a query format as in zephyr.
```
<|user|>
Что такое мем?</s>
<|assistant|>
Мем - это культурный феномен, который может быть описан как информационный вирус. Он представляет собой абстрактный элемент культуры или идеи в виде изображения (обычно с изображением человека) и его краткого текста на основе которого можно создать мемы различных форматов: от графических до текстовых шуток; мема могут использоваться для передачи определенных идей через интернет-сообщество без необходимости использовать слова напрямую!</s>
```
Check out the [space](https://huggingface.co./spaces/0x7194633/fialka) to use the model in UI without downloading.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_0x7194633__fialka-7B-v3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |46.40|
|AI2 Reasoning Challenge (25-Shot)|48.55|
|HellaSwag (10-Shot)              |71.05|
|MMLU (5-Shot)                    |43.06|
|TruthfulQA (0-shot)              |44.79|
|Winogrande (5-shot)              |69.46|
|GSM8k (5-shot)                   | 1.52|