---
language:
- ru
datasets:
- IlyaGusev/saiga_scored
- IlyaGusev/saiga_preferences
license: apache-2.0
---


# Saiga/MistralNemo 12B, Russian fine-tune of Mistral Nemo

Based on [an abliterated version](https://huggingface.co/natong19/Mistral-Nemo-Instruct-2407-abliterated) of [Mistral Nemo](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407).

Llama.cpp version: TBD

Colab: [link](https://colab.research.google.com/drive/1vNzMyPqx2GB7zk3ANDtZEfvhzgYOWu0B)

## Prompt format

Original Misral Nemo prompt format, but the system prompt is in the beginning:
```
<s>Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.
[INST]Как дела?[/INST]
Отлично, а у тебя?</s>
[INST]Шикарно. Как пройти в библиотеку?[/INST] 
```

## Code example
```python
# Исключительно ознакомительный пример.
# НЕ НАДО ТАК ИНФЕРИТЬ МОДЕЛЬ В ПРОДЕ.
# См. https://github.com/vllm-project/vllm или https://github.com/huggingface/text-generation-inference

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig

MODEL_NAME = "IlyaGusev/saiga_nemo_12b"

model = AutoModelForCausalLM.from_pretrained(
    MODEL_NAME,
    load_in_8bit=True,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
model.eval()

tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
generation_config = GenerationConfig.from_pretrained(MODEL_NAME)
print(generation_config)

inputs = ["Почему трава зеленая?", "Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч"]
for query in inputs:
    prompt = tokenizer.apply_chat_template([{
        "role": "user",
        "content": query
    }], tokenize=False, add_generation_prompt=True)
    data = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
    data = {k: v.to(model.device) for k, v in data.items()}
    data.pop("token_type_ids", None)
    output_ids = model.generate(**data, generation_config=generation_config)[0]
    output_ids = output_ids[len(data["input_ids"][0]):]
    output = tokenizer.decode(output_ids, skip_special_tokens=True).strip()
    print(query)
    print(output)
    print()
    print("==============================")
    print()
```

## Output examples
```
User: Почему трава зеленая? 
Saiga: TBD
```

```
User: Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч
Saiga: TBD
```


## Versions
v1:
- [87a83ce252ff0142cd4cc918fb3e6a9875ca4638](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/87a83ce252ff0142cd4cc918fb3e6a9875ca4638)
- Other name: saiga_nemo_12b_sft_m9_d14_simpo_m19_d31 
- SFT dataset config: [sft_d14.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d14.json)
- SFT model config: [saiga_nemo_12b_sft_m9.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m9.json)
- SimPO dataset config: [pref_d31.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d31.json)
- SimPO model config: [saiga_nemo_12b_simpo_m19.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m19.json)
- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/e74ozfzh)
- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/b094iiej)


## Evaluation

RuArenaHard:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/-uG--3Wu9oUi9_bC_ZFP4.png)


PingPing:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/uNmD2YhealySO6UYUH8-g.png)