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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zst filter=lfs diff=lfs merge=lfs -text
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+tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,93 @@
+---
+license: apache-2.0
+base_model: Wan-AI/Wan2.2-T2V-A14B-Diffusers
+pipeline_tag: text-to-video
+library_name: mlx-gen
+tags:
+- mlx
+- mlx-gen
+- mflux
+- apple-silicon
+- 8-bit
+- wan
+- wan2.2
+- video-generation
+- text-to-video
+- image-to-video
+- wan-a14b
+---
+# wan2.2-t2v-a14b-diffusers-8bit
+
+This repository contains MLX-Gen saved weights for `Wan-AI/Wan2.2-T2V-A14B-Diffusers`. The checkpoint is designed for local Apple Silicon inference with [`mlx-gen`](https://github.com/lpalbou/mlx-gen).
+
+It uses the mflux/MLX saved-weight layout and MLX quantization tensors. It is not a Diffusers or Transformers `from_pretrained()` checkpoint.
+
+## Source Model
+
+Original model: [`Wan-AI/Wan2.2-T2V-A14B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B-Diffusers).
+
+## License and Access
+
+This quantized derivative follows the Apache 2.0 license of the source model.
+
+## Quantization
+
+This is an MLX q8 checkpoint for Wan2.2 A14B. MLX-Gen uses 8-bit quantization for Wan modules where MLX supports quantization:
+
+- q8 for quantizable Wan transformer attention and feed-forward modules.
+- BF16 for the Wan VAE.
+- BF16 for Wan transformer conditioning/output projection linears, the UMT5 text encoder, scheduler metadata, tokenizer files, norms, and other non-quantizable parameters.
+
+Wan q4 quality and any possible mixed q4/q8 policy are still under validation. Prefer q8 for publishable Wan checkpoints until the q4 policy is documented.
+
+See the [MLX-Gen quantization docs](https://github.com/lpalbou/mlx-gen/blob/main/docs/quantization.md) for compatibility notes.
+
+## Local Validation
+
+Validation used 384x224, 17 frames, 12 denoising steps, guidance 4, guidance-2 3, fps 8, and seed 4242 on Apple Silicon. Memory is measured for the full package run from model init through video save. RSS alone is not enough for MLX/Metal unified-memory pressure, so the table reports both MLX allocator peak and Darwin physical footprint.
+
+| Package | Folder Size | Runtime Precision | Mode | MLX Peak | Physical Footprint Peak | Time | Notes |
+| --- | ---: | --- | --- | ---: | ---: | ---: | --- |
+| Upstream source snapshot | 118 GiB | BF16 runtime from FP32/BF16 source files | release inactive denoiser | 32.99 GiB | 48.90 GiB | 108.31 s | Baseline source-cache run. |
+| BF16 prepared folder | 64 GiB | BF16 | release inactive denoiser | 32.98 GiB | 45.12 GiB | 114.39 s | Output was byte-identical to the source-cache run. |
+| This mixed q8/BF16 folder | 40 GiB | q8 transformer block linears, BF16 sensitive paths and VAE | release inactive denoiser | 20.84 GiB | 31.75 GiB | 110.34 s | Lower usage memory; not byte-identical to BF16 but passed side-by-side validation. |
+| This mixed q8/BF16 folder | 40 GiB | q8 transformer block linears, BF16 sensitive paths and VAE | no denoiser release | 35.19 GiB | 50.55 GiB | 108.10 s | Retains both quantized A14B denoisers through decode. |
+| This mixed q8/BF16 folder | 40 GiB | q8 transformer block linears, BF16 sensitive paths and VAE | low-RAM release | 15.48 GiB | 20.74 GiB | 108.70 s | Lowest measured usage-memory mode. |
+
+Within each package/precision, release/no-release/low-RAM outputs were byte-identical. This prepared q8 folder was also byte-identical to runtime `--quantize 8` from the upstream source snapshot. q8 is not byte-identical to BF16, but the validation contact sheet stayed in the same visual family.
+
+## Compatibility
+
+Requires `mlx-gen >= 0.18.8`.
+
+Generated with `mlx-gen 0.18.8`.
+
+Use the `mlxgen` command and Python import path for new MLX-Gen projects.
+
+## Usage
+
+```bash
+python -m pip install -U mlx-gen
+
+mlxgen download --model AbstractFramework/wan2.2-t2v-a14b-diffusers-8bit
+
+mlxgen generate \
+  --model AbstractFramework/wan2.2-t2v-a14b-diffusers-8bit \
+  --task text-to-video \
+  --prompt "Your video prompt here" \
+  --width 1280 \
+  --height 720 \
+  --frames 81 \
+  --steps 40 \
+  --guidance 4 \
+  --guidance-2 3 \
+  --fps 16 \
+  --seed 42 \
+  --output video.mp4
+```
+
+## Attribution
+
+MLX-Gen is based on [mflux](https://github.com/filipstrand/mflux) by Filip Strand and the original mflux contributors. This model card is generated by MLX-Gen so derived checkpoints keep that attribution visible.
+
+Quantized and contributed by [@lpalbou](https://huggingface.co/lpalbou).

model_index.json

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+{
+  "_class_name": "WanPipeline",
+  "_diffusers_version": "0.35.0.dev0",
+  "boundary_ratio": 0.875,
+  "scheduler": [
+    "diffusers",
+    "UniPCMultistepScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "UMT5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "T5TokenizerFast"
+  ],
+  "transformer": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "transformer_2": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLWan"
+  ]
+}

scheduler/scheduler_config.json

@@ -0,0 +1,30 @@
+{
+  "_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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