README.md

metadata

base_model: driaforall/mem-agent
library_name: mlx
pipeline_tag: text-generation
tags:
  - mlx

driaforall/mem-agent-mlx-quant

This model driaforall/mem-agent-mlx-4bit was converted to MLX format from driaforall/mem-agent using mlx-lm version 0.25.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("driaforall/mem-agent-mlx-quant")

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)