LFM2.5-VL-3B-MLX-4bit
MLX export of LFM2.5-VL-3B for Apple Silicon inference.
LFM2.5-VL-3B is a vision-language model built on the LFM2.5-2.6B backbone with a SigLIP2 NaFlex vision encoder (400M). It supports OCR, document comprehension, multilingual vision understanding, bounding box prediction, and function calling.
Model Details
| Property | Value |
|---|---|
| Parameters | 3B |
| Precision | 4-bit |
| Group Size | 64 |
| Size | 2.2 GB |
| Context Length | 32K |
| Vision Encoder | SigLIP2 NaFlex (400M) |
| Native Resolution | up to 512x512 |
Quickstart
uv pip install 'mlx-vlm'
uv run --with mlx-vlm mlx_vlm.generate --model LiquidAI/LFM2.5-VL-3B-MLX-4bit --max-tokens 100 --temperature 0.2 --image https://placecats.com/neo/300/200 --prompt "how many animals are in the picture?"
from mlx_vlm import apply_chat_template, generate, load
from mlx_vlm.utils import load_image
model, processor = load("LiquidAI/LFM2.5-VL-3B-MLX-4bit")
image = load_image("https://placecats.com/neo/300/200")
messages = [
{
"role": "user",
"content": [
{"type": "image"},
{"type": "text", "text": "What do you see in this image?"},
],
}
]
prompt = apply_chat_template(
processor,
model.config,
messages,
add_generation_prompt=True,
num_images=1,
)
result = generate(
model,
processor,
prompt,
[image],
temp=0.2,
top_k=50,
repetition_penalty=1.0,
verbose=True,
)
print(result.text)
Recommended Sampling Parameters
| Parameter | Value |
|---|---|
| temperature | 0.2 |
| top_k | 50 |
| repetition_penalty | 1.0 |
License
This model is released under the LFM 1.0 License.