Add model card

README.md

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+---
+license: apache-2.0
+base_model: black-forest-labs/FLUX.2-klein-4B
+base_model_relation: quantized
+pipeline_tag: text-to-image
+library_name: coreai
+tags:
+  - coreai
+  - ios
+  - text-to-image
+  - flux
+  - react-native
+---
+
+# FLUX.2 klein 4B for Core AI on iPhone
+
+[black-forest-labs/FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B) (4B parameters, step-distilled text-to-image) exported to Apple Core AI for iOS with the [`apple/coreai-models`](https://github.com/apple/coreai-models) recipe. It runs on iOS 27 and macOS 27 with the `FlowTransformerPipeline` from the `CoreAIDiffusion` product of `coreai-models`, and generates 512x512 images in 4 steps.
+
+## Files
+
+`ios/` holds the text-to-image components of the recipe's iOS export, 4-bit weights (4.0 GB):
+
+| File | Size | |
+| --- | --- | --- |
+| `Transformer_512.aimodel` | 2.0 GB | DiT, 25 blocks, 512x512 |
+| `TextEncoder.aimodel` | 1.6 GB | Qwen3 text encoder |
+| `VAEDecoder_half.aimodel` | 95 MB | latent to 512x512 image |
+| `tokenizer/`, `metadata.json`, `vae_bn_*.npy` | 11 MB | |
+
+The image-to-image transformer and VAE encoder of the full iOS export are left out. The pipeline loads one component at a time by default (`lazyModelLoading`), so it fits in the memory an iPhone 17 Pro gives an app.
+
+## Use
+
+With [`@react-native-ai/core-ai`](https://github.com/callstackincubator/ai), download the `ios` folder and pass its path:
+
+```typescript
+import { coreAI } from '@react-native-ai/core-ai'
+import { generateImage } from 'ai'
+
+const { image } = await generateImage({
+  model: coreAI.imageModel({
+    id: 'flux2-klein-4b',
+    source: { type: 'file', uri: fluxModelPath },
+  }),
+  prompt: 'a red apple on a wooden table',
+  size: '512x512',
+  seed: 42,
+  providerOptions: { 'core-ai': { stepCount: 4 } },
+})
+```
+
+In Swift:
+
+```swift
+import CoreAIDiffusionPipeline
+
+let pipeline = try await FlowTransformerPipeline(from: modelURL)
+let configuration = PipelineConfiguration(
+    prompt: "a red apple on a wooden table",
+    seed: 42,
+    stepCount: 4,
+    guidanceScale: 1.0,
+    schedulerType: .discreteFlow
+)
+let image = try await pipeline.generateImages(configuration: configuration) { _ in true }.images[0]
+```
+
+## Export
+
+From [`apple/coreai-models`](https://github.com/apple/coreai-models) at `5de95c6` (1.0.0), with `coreai-core` 1.0.0b3. This is `--platform iOS` (4-bit, single-function, 512) without the image-to-image components:
+
+```bash
+uv run coreai.diffusion.export flux2-klein-4b --single-function \
+    --components transformer_512 text_encoder vae_decoder_half
+```
+
+## License
+
+Apache-2.0, as the original model. The weights were converted to Core AI and quantized to 4 bits, and are otherwise unchanged. FLUX.2 [klein] is by [Black Forest Labs](https://bfl.ai).