README.md

metadata

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 was converted to MLX format from Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct using mlx-lm version 0.20.1.

Use with mlx

pip install mlx-lm

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)