README.md

metadata

library_name: mlx
license: apache-2.0
pipeline_tag: image-text-to-text
base_model:
  - google/gemma-4-E2B-it
base_model_relation: quantized
tags:
  - gemma4
  - mlx
  - apple-silicon
  - 8bit
  - on-device
  - conversational

LetheanNetwork/lemer-mlx-8bit

Gemma 4 E2B in MLX format, 8-bit quantized, converted from LetheanNetwork/lemer's bf16 safetensors via mlx_lm.convert. Higher-precision sibling of LetheanNetwork/lemer-mlx (which is 4-bit). For the LEK-merged variant see lthn/lemer.

Variants in this family

Repo	Format	Bits	Use case
LetheanNetwork/lemer	safetensors + gguf Q4_K_M	bf16 / 4	Source weights + llama.cpp/Ollama
LetheanNetwork/lemer-mlx	mlx	4	Apple Silicon default
LetheanNetwork/lemer-mlx-8bit	mlx	8	This repo — higher precision
LetheanNetwork/lemer-mlx-bf16	mlx	bf16	Full-precision reference

Usage

from mlx_lm import load, generate

model, tokenizer = load("LetheanNetwork/lemer-mlx-8bit")
response = generate(
    model, tokenizer,
    prompt=tokenizer.apply_chat_template(
        [{"role": "user", "content": "Hello"}],
        add_generation_prompt=True,
        enable_thinking=True,
    ),
    max_tokens=512,
)

Provenance

• Source: LetheanNetwork/lemer bf16 safetensors (= google/gemma-4-E2B-it)
• Converter: mlx_lm.convert (mlx-lm — LM Studio / Apple ML Research)
• Quant: 8-bit group quantization, ~8.5 bits/weight effective
• License: Apache 2.0 (Gemma Terms of Use)

License

Apache 2.0, subject to the Gemma Terms of Use.