LiquidAI/LFM2.5-350M-MLX-8bit
<div align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" alt="Liquid AI" style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;" /> <div style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;"> <a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> • <a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> • <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> • <a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a> </div> </div> <br>
LFM2.5-350M-MLX-8bit
MLX export of LFM2.5-350M for Apple Silicon inference.
LFM2.5-350M is a compact multilingual base model built on LiquidAI's hybrid architecture, combining convolutional and attention layers for efficient long-context processing.
Model Details
Use with mlx
pip install mlx-lmfrom mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler
model, tokenizer = load("LiquidAI/LFM2.5-350M-MLX-8bit")
response = generate(
model,
tokenizer,
prompt="The capital of France is",
max_tokens=100,
sampler=make_sampler(temp=0.7),
verbose=True,
)Other Precisions
- LFM2.5-350M-MLX-bf16 (676 MB)
- LFM2.5-350M-MLX-8bit (381 MB)
- LFM2.5-350M-MLX-6bit (296 MB)
- LFM2.5-350M-MLX-5bit (254 MB)
- LFM2.5-350M-MLX-4bit (212 MB)
License
This model is released under the LFM 1.0 License.
