LM (MLX)
Collection
State-Space-Model powered Language Models for Apple Silicon
•
12 items
•
Updated
•
4
This is an MLX-compatible version of the mamba2-780m model, quantized to 8 bits. It uses the EleutherAI/gpt-neox-20b tokenizer. For more details, see our blog post.
This model requires the cartesia-metal
and cartesia-mlx
packages.
Installation requires Xcode, which can be downloaded from https://developer.apple.com/xcode/. Accept the license agreement with:
sudo xcodebuild -license
Install the required dependencies: the exact version of nanobind
, followed by cartesia-metal
, and finally cartesia-mlx
, with the following commands:
pip install nanobind@git+https://github.com/wjakob/nanobind.git@2f04eac452a6d9142dedb957701bdb20125561e4
pip install git+https://github.com/cartesia-ai/edge.git#subdirectory=cartesia-metal
pip install cartesia-mlx
Note: This package has been tested on macOS Sonoma 14.1 with the M3 chip.
import mlx.core as mx
import cartesia_mlx as cmx
model = cmx.from_pretrained("cartesia-ai/mamba2-780m-8bit-mlx")
model.set_dtype(mx.float32)
prompt = "Rene Descartes was"
print(prompt, end="", flush=True)
for text in model.generate(
prompt,
max_tokens=500,
eval_every_n=5,
verbose=True,
top_p=0.99,
temperature=0.85,
):
print(text, end="", flush=True)
At Cartesia, we're building real-time multimodal intelligence for every device.