---
license: apache-2.0
datasets:
- dichspace/darulm
- HuggingFaceFW/fineweb-2
- RefalMachine/hybrid_reasoning_dataset_ru
language:
- ru
- en
base_model: RefalMachine/RuadaptQwen3-32B-Instruct
library_name: mlx
tags:
- mlx
pipeline_tag: text-generation
---

# Bogdan01m/RuadaptQwen3-32B-Instruct-MLX-8bit

This model [Bogdan01m/RuadaptQwen3-32B-Instruct-MLX-8bit](https://huggingface.co/Bogdan01m/RuadaptQwen3-32B-Instruct-MLX-8bit) was
converted to MLX format from [RefalMachine/RuadaptQwen3-32B-Instruct](https://huggingface.co/RefalMachine/RuadaptQwen3-32B-Instruct)
using mlx-lm version **0.28.3**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("Bogdan01m/RuadaptQwen3-32B-Instruct-MLX-8bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```

## Citation

```bibtex
@article{tikhomirov2024facilitating,
  title={Facilitating Large Language Model Russian Adaptation with Learned Embedding Propagation},
  author={Tikhomirov, Mikhail and Chernyshov, Daniil},
  journal={Journal of Language and Education},
  volume={10},
  number={4},
  pages={130--145},
  year={2024}
}
```