Instructions to use MLXBits/10eros-experimental-mlx-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLXBits/10eros-experimental-mlx-q8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MLXBits/10eros-experimental-mlx-q8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - MLX
How to use MLXBits/10eros-experimental-mlx-q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir 10eros-experimental-mlx-q8 MLXBits/10eros-experimental-mlx-q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
10Eros Experimental MLX Q8
10Eros v1 for Apple Silicon via ltx-2-mlx, with the Sulphur experimental LoRA fused at 0.35 strength.
This is an 8-bit quantization, targeted at 32GB+ Macs running Apple Silicon. If there is any interest in a 4-bit quant, use the community tab to request one, noting your Mac's spec. In my experience, 32GB M-series is the low bar for using anything based on LTX2.3.
Model Contents
| File | Contents |
|---|---|
transformer-dev.safetensors |
10Eros base + Sulphur Experimental Lora @ 0.35 |
transformer-distilled-1.1.safetensors |
10Eros base + Sulphur @ 0.35 + 10Eros condsafe distilled LoRA @ 1.0 |
How It Was Built
Step 1 โ Sulphur merge (bf16)
The Sulphur experimental LoRA was merged into 10Eros_v1_bf16.safetensors at strength 0.35 using a custom merge_lora.py script. This produces the dev transformer source.
Step 2 โ Condsafe distilled merge (bf16)
TenStrip's condsafe distilled LoRA (ltx-2.3-22b-distilled-lora-1.1_fro90_ceil72_condsafe.safetensors) was merged into the Step 1 output at strength 1.0. This produces the distilled transformer source.
The standard distilled-384 LoRAs from Lightricks are incompatible with 10Eros โ they produce a frosted-glass texture artifact. TenStrip's condsafe LoRA is specifically designed to work with this finetune.
Step 3 โ MLX conversion + quantization
Converted with mlx-forge:
# Distilled transformer + shared components
mlx-forge convert ltx-2.3 \
--checkpoint 10eros-experimental-distilled-bf16.safetensors \
--variant distilled-1.1 --quantize --bits 8 \
--spatial-upscaler x2 x1.5 --temporal-upscaler x2 \
--output 10eros-experimental-mlx-q8
# Dev transformer (added to same directory)
mlx-forge convert ltx-2.3 \
--checkpoint 10eros-experimental-bf16.safetensors \
--variant dev --quantize --bits 8 --skip-shared \
--output 10eros-experimental-mlx-q8
Usage
# Distilled (fast, recommended)
ltx-2-mlx generate --model MLXBits/10eros-experimental-mlx-q8 \
--distilled --prompt "your prompt" --low-ram -o output.mp4
# One-stage dev (slower, CFG)
ltx-2-mlx generate --model MLXBits/10eros-experimental-mlx-q8 \
--one-stage --prompt "your prompt" --low-ram -o output.mp4
Credits
- 10Eros v1: TenStrip/LTX2.3-10Eros
- Sulphur 2 Experimental LoRA: SulphurAI/Sulphur-2-base
- MLX conversion: mlx-forge
- Inference: ltx-2-mlx
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Quantized
Model tree for MLXBits/10eros-experimental-mlx-q8
Base model
TenStrip/LTX2.3-10Eros