Views
No views yet
.pte program per backend (XNNPACK, Core ML, MLX), ready for use in the ExecuTorch runtime.useTextToImage hook / models.textToImage.SDXS_512_DREAMSHAPER constant. If you'd like to run these models in your own ExecuTorch runtime, refer to the official documentation..pte files. These models were exported for the v0.10.0 release; no forward compatibility is guaranteed. When using React Native ExecuTorch, the library constants guarantee compatibility with the runtime used behind the scenes..pte exports three methods (see the per-backend config.json for exact shapes/dtypes):encode — CLIP text token ids int64 [1, 77] → text embeddings float32 [1, 77, 768].denoise — latents float32 [1, 4, 64, 64], timestep int64 [1], embeddings float32 [1, 77, 768] → predicted noise float32 [1, 4, 64, 64].decode — latents float32 [1, 4, 64, 64] → image float32 [1, 3, 512, 512] in [0, 1].xnnpack/, coreml/, mlx/ — one multi-method .pte per backend plus a config.json declaring its variants and method contract.tokenizer.json, tokenizer_config.json — the CLIP tokenizer, in the repository root.config.json — top-level model descriptor.