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This folder contains a converted MLX version of the ftplaces2 Moebius checkpoint in mxfp8 form. ftplaces2 means the Moebius checkpoint fine-tuned on Places2, for general scene, background, and object inpainting.
Modellquelle
Quellenbeschreibung
This folder contains a converted MLX version of the ft_places2 Moebius checkpoint in mxfp8 form. ft_places2 means the Moebius checkpoint fine-tuned on Places2, for general scene, background, and object inpainting.
Original upstream model: Original source repository:
Quellen
1 QuelleVerifiziert 31. Juli
Modellartefakte
1 Artefaktunet_quantized.safetensors
safetensors · 412 MB · SHA-256 4e9db583f4a1…93e2 · Hugging Face
HerunterladenQuellenauszüge
2 AuszügeMoebius checkpoint fine-tuned on Places2. This is the general scene, background, and object inpainting variant converted from the original PyTorch checkpoint.
| Field | Value |
|---|---|
| Variant name | ft_places2-mxfp8 |
| Checkpoint meaning | Fine-tuned on Places2 for general scene, background, and object inpainting. |
| Original Moebius checkpoint family | ft_places2 |
| Original checkpoint type | Places2 fine-tune |
| Source PyTorch checkpoint | Moebius-Models/ft_places2/diffusion_pytorch_model.bin |
| MLX precision / quantization label | mxfp8 |
| Image size | 512 x 512 |
| Latent size | 64 x 64 |
| Latent channels | 4 |
| Mask channels | 1 |
| Conditioning IDs | 20 |
| VAE scaling factor |
MLX MXFP8-style 8-bit export. The manifest selects unet_quantized.safetensors; VAE encoder and decoder remain regular f16 safetensors. Runtime quantization metadata uses mode: mxfp8 with group size 32.
mxfp8.mxfp8 mode.These are the files selected by manifest.json when the Moebius-MLX runtime loads this variant.
| Component | File | Size |
|---|---|---|
| UNet | unet_quantized.safetensors | 432.23 MB |
| VAE encoder | vae_encoder.safetensors | 68.34 MB |
| VAE decoder | vae_decoder.safetensors | 99.00 MB |
unet.safetensorsunet_quantized.safetensors (selected by manifest)vae_decoder.safetensors (selected by manifest)vae_encoder.safetensors (selected by manifest)manifest.json (runtime metadata and file selection)A minimal runtime package needs manifest.json and the manifest-selected files above. Extra source or fallback files are optional and are not required for inference.
This is not a Transformers or Diffusers-native checkpoint. It is intended for the Swift/MLX runtime in Moebius-MLX. The runtime reads manifest.json, loads the selected safetensors files, builds the Moebius UNet and VAE modules, and runs the DDIM inpainting pipeline.
Pipeline constants must match the manifest:
scaled_linear, beta start 0.00085, beta end 0.012, 1000 train timesteps, clip sample falseMoebius was released by the original authors as hustvl/Moebius. This folder is a format conversion and/or quantized MLX packaging of the original PyTorch weights, not a newly trained model.
Anforderungen
2 AnforderungenVAE · Hugging Face · iky1e/moebius-ft-places2-mlx-mxfp8
VAE · Hugging Face · iky1e/moebius-ft-places2-mlx-mxfp8
--- license: apache-2.0 library_name: mlx pipeline_tag: image-to-image base_model: hustvl/Moebius tags: - mlx - image-inpainting - inpainting - diffusion - moebius - ft_places2 - mxfp8 --- # Moebius ft_places2 MLX mxfp8 This folder contains a converted MLX version of the **ft_places2** Moebius checkpoint in **mxfp8** form. `ft_places2` means the Moebius checkpoint fine-tuned on Places2, for general scene, background, and object inpainting. Original upstream model: [hustvl/Moebius](https://huggingface.co/hustvl/Moebius) Original source repository: [hustvl/Moebius](https://github.com/hustvl/Moebius) Moebius checkpoint fine-tuned on Places2. This is the general scene, background, and object inpainting variant converted from the original PyTorch checkpoint. ## Identity | Field | Value | |---|---| | Variant name | `ft_places2-mxfp8` | | Checkpoint meaning | Fine-tuned on Places2 for general scene, background, and object inpainting. | | Original Moebius checkpoint family | `ft_places2` | | Original checkpoint type | Places2 fine-tune | | Source PyTorch checkpoint | `Moebius-Models/ft_places2/diffusion_pytorch_model.bin` | | MLX precision / quantization label | `mxfp8` | | Image size | 512 x 512 | | Latent size | 64 x 64 | | Latent channels | 4 | | Mask channels | 1 | | Conditioning IDs | 20 | | VAE scaling factor | 0.13025 | | Noise offset | 0.0357 | ## Quantization MLX MXFP8-style 8-bit export. The manifest selects `unet_quantized.safetensors`; VAE encoder and decoder remain regular f16 safetensors. Runtime quantization metadata uses `mode: mxfp8` with group size 32. - UNet precision mode: `mxfp8`. - MLX grouped quantization is used for supported linear layers; grouped quantized weights are loaded through the Moebius-MLX manifest/runtime. - Quantization config: 8 bits, group size 32, `mxfp8` mode. - The VAE encoder and decoder remain regular f16 safetensors for this variant. ## Manifest-selected deployment files These are the files selected by `manifest.json` when the Moebius-MLX runtime loads this variant. | Component | File | Size | |---|---|---:| | UNet | `unet_quantized.safetensors` | 432.23 MB | | VAE encoder | `vae_encoder.safetensors` | 68.34 MB | | VAE decoder | `vae_decoder.safetensors` | 99.00 MB | ## Files in this folder - `unet.safetensors` - `unet_quantized.safetensors` (selected by manifest) - `vae_decoder.safetensors` (selec...
Source context: 0 downloads · 0 likes · Pipeline image-to-image · Library mlx · Repo iky1e/moebius-ft-places2-mlx-mxfp8
| 0.13025 |
| Noise offset | 0.0357 |