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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/i2v_takeoff_source.png filter=lfs diff=lfs merge=lfs -text
+tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,99 @@
+---
+license: apache-2.0
+base_model: Wan-AI/Wan2.2-I2V-A14B-Diffusers
+pipeline_tag: image-to-video
+library_name: mlx-gen
+tags:
+- mlx
+- mlx-gen
+- mflux
+- apple-silicon
+- 8-bit
+- mixed-q8-bf16
+- wan
+- wan2.2
+- video-generation
+- image-to-video
+- wan-a14b
+---
+# wan2.2-i2v-a14b-diffusers-8bit
+
+This repository contains mixed q8/BF16 MLX-Gen saved weights for
+[`Wan-AI/Wan2.2-I2V-A14B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B-Diffusers).
+It is designed for local Apple Silicon inference with
+[`mlx-gen`](https://github.com/lpalbou/mlx-gen).
+
+It uses the mflux/MLX saved-weight layout with MLX quantization tensors. It is not a Diffusers or Transformers
+`from_pretrained()` checkpoint.
+
+## Source Model
+
+Original model: [`Wan-AI/Wan2.2-I2V-A14B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B-Diffusers).
+
+This quantized derivative follows the Apache 2.0 license of the source model.
+
+## Quantization
+
+This is a mixed q8/BF16 checkpoint:
+
+- q8 for quantizable Wan transformer block attention and feed-forward linears.
+- BF16 for the Wan VAE.
+- BF16 for Wan transformer conditioning/output projection linears, the UMT5 text encoder, scheduler metadata, tokenizer files, norms, convolutions, and other non-quantizable parameters.
+
+This mixed policy is used because fully quantizing sensitive Wan A14B paths produced invalid or low-quality video in local validation.
+
+## Validation
+
+Measured on 2026-06-04 with `mlx-gen 0.18.9` on Apple Silicon. The upstream Diffusers source snapshot measured about 118 GiB in the local Hugging Face cache before preparing these packages. The table below reports prepared-package generation from model init through MP4 save and post-save video-health validation.
+
+Validation profile: public spacecraft source image, `384x384`, 33 frames, 12 denoising steps, guidance `3.5`, guidance-2 `3.5`, 8 fps, seed `4242`, `--low-ram`.
+
+| Package | Disk | Full-Process Physical Peak | Max RSS | MLX Peak | Total Time | Video Health |
+|---|---:|---:|---:|---:|---:|---|
+| BF16 package | 64.1 GiB | 33.7 GiB | 31.8 GiB | 28.2 GiB | 228.2 s | 33/33 frames, 384x384, 8 fps, temporal delta 10.4 |
+| This mixed q8/BF16 package | 39.7 GiB | 21.5 GiB | 19.6 GiB | 15.9 GiB | 242.2 s | 33/33 frames, 384x384, 8 fps, temporal delta 10.5 |
+
+Compared with the BF16 prepared package at the same validation profile, this mixed q8/BF16 package reduces disk usage by about 38% and full-process physical peak memory by about 36%. Total time was about 6% slower in this run.
+
+Physical peak is Darwin `ri_phys_footprint` sampled for the full process. The validation is intentionally small and repeatable; it is not a claim that every full-size `1280x720`, 81-frame, 40-step job has the same memory or timing profile.
+
+## Usage
+
+The included public sample image is available at `examples/i2v_takeoff_source.png` when this repository is cloned locally. For best I2V stability, use an input image whose aspect ratio matches the requested video dimensions and keep the subject inside the frame.
+
+```bash
+python -m pip install -U mlx-gen
+
+mlxgen download --model AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit
+
+mlxgen generate \
+  --model AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit \
+  --task image-to-video \
+  --image path/to/input.png \
+  --prompt "Cinematic image-to-video of the spacecraft lifting off from a snowy landing field, engines glowing, exhaust plume expanding, the full craft remains centered in frame." \
+  --width 384 \
+  --height 384 \
+  --frames 33 \
+  --steps 12 \
+  --guidance 3.5 \
+  --guidance-2 3.5 \
+  --fps 8 \
+  --seed 4242 \
+  --low-ram \
+  --metadata \
+  --output video.mp4
+```
+
+## Compatibility
+
+Requires `mlx-gen >= 0.18.9`.
+
+Generated with `mlx-gen 0.18.9`.
+
+Use the `mlxgen` command and Python import path for new MLX-Gen projects.
+
+## Attribution
+
+MLX-Gen is based on [mflux](https://github.com/filipstrand/mflux) by Filip Strand and the original mflux contributors.
+
+Quantized and contributed by [@lpalbou](https://huggingface.co/lpalbou).

model_index.json

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+{
+  "_class_name": "WanImageToVideoPipeline",
+  "_diffusers_version": "0.35.0.dev0",
+  "boundary_ratio": 0.9,
+  "image_encoder": [
+    null,
+    null
+  ],
+  "image_processor": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "UniPCMultistepScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "UMT5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "T5TokenizerFast"
+  ],
+  "transformer": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "transformer_2": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLWan"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "UniPCMultistepScheduler",
+  "_diffusers_version": "0.35.0.dev0",
+  "beta_end": 0.02,
+  "beta_schedule": "linear",
+  "beta_start": 0.0001,
+  "disable_corrector": [],
+  "dynamic_thresholding_ratio": 0.995,
+  "final_sigmas_type": "zero",
+  "flow_shift": 3.0,
+  "lower_order_final": true,
+  "num_train_timesteps": 1000,
+  "predict_x0": true,
+  "prediction_type": "flow_prediction",
+  "rescale_betas_zero_snr": false,
+  "sample_max_value": 1.0,
+  "solver_order": 2,
+  "solver_p": null,
+  "solver_type": "bh2",
+  "steps_offset": 0,
+  "thresholding": false,
+  "time_shift_type": "exponential",
+  "timestep_spacing": "linspace",
+  "trained_betas": null,
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": false,
+  "use_exponential_sigmas": false,
+  "use_flow_sigmas": true,
+  "use_karras_sigmas": false
+}

text_encoder/config.json

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+{
+  "_name_or_path": "google/umt5-xxl",
+  "architectures": [
+    "UMT5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 10240,
+  "d_kv": 64,
+  "d_model": 4096,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "umt5",
+  "num_decoder_layers": 24,
+  "num_heads": 64,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "scalable_attention": true,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.48.0.dev0",
+  "use_cache": true,
+  "vocab_size": 256384
+}

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