How to use from the
Use from the
MLX library
# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("dokterbob/iFlow-ROME-mlx-mxfp4")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

dokterbob/iFlow-ROME-mlx-mxfp4

This model dokterbob/iFlow-ROME-mlx-mxfp4 was converted to MLX format from FutureLivingLab/iFlow-ROME using mlx-lm version 0.31.0.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("dokterbob/iFlow-ROME-mlx-mxfp4")

prompt = "hello"

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

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