README.md

---
library_name: transformers
model_name: Vikhr-Qwen-2.5-1.5B-Instruct
base_model: Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct
language:
- ru
- en
license: apache-2.0
datasets:
- Vikhrmodels/GrandMaster-PRO-MAX
tags:
- mlx
---

# Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_4bit

The Model [Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_4bit](https://huggingface.co/Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_4bit) was
converted to MLX format from [Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct](https://huggingface.co/Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct)
using mlx-lm version **0.20.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_4bit")

prompt="hello"

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

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