README.md

metadata

library_name: transformers
model_name: Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r
base_model: Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r
language:
  - ru
  - en
license: apache-2.0
datasets:
  - Vikhrmodels/russian_math
  - openai/gsm8k
tags:
  - mlx

Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r_MLX-4bit

The Model Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r_MLX-4bit was converted to MLX format from Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r using mlx-lm version 0.21.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r_MLX-4bit")

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)