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---
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_8bit
The Model [Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_8bit](https://huggingface.co/Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct-MLX_8bit) 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_8bit")
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)
```
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