Bundle the Apache-2.0 Flux.2 VAE so the model is usable in one download

vae/ is an unmodified, byte-identical copy of black-forest-labs/FLUX.2-klein-base-4B vae/diffusion_pytorch_model.safetensors (sha256 ca70d220...) and its config.json, redistributed under Apache-2.0 with the licence text as LICENSE-FLUX2-VAE.md and attribution in the model card. Users no longer need a separate, gated download to encode or decode latents. The DiT weights are unchanged.

LICENSE-FLUX2-VAE.md

@@ -0,0 +1,176 @@
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README.md

@@ -49,6 +49,7 @@ and longitude.
 |---|---|
 | Parameters | 9.24 B |
 | Weights | final training weights (non-EMA), bfloat16, sharded safetensors |
+| Included | frozen Flux.2 VAE in `vae/` (Apache-2.0, Black Forest Labs) |
 | Architecture | Flow Matching DiT — 8 double-stream + 24 single-stream blocks, hidden 4096, 32 heads |
 | Conditioning | CLIP + T5 text embeddings, GSD, latitude, longitude |
 | Training data | [Git-10M](https://huggingface.co/datasets/lcybuaa/Git-10M) |
@@ -84,7 +85,7 @@ metadata, is provided by `inference.py`:
 ```bash
 python inference.py \
     --ckpt /path/to/GeoCore-9B \
-    --vae FLUX.2-klein-base-4B/vae/diffusion_pytorch_model.safetensors \
+    --vae /path/to/GeoCore-9B/vae \
     --prompt "A satellite view of a highly dense urban city with towering skyscrapers" \
     --lon 126.97 --lat 37.56 --res 0.0 \
     --num-samples 4 --out samples/
@@ -98,26 +99,30 @@ python inference.py \
 * Any field set to `-999.0` falls back to the model's learned null embedding for that field, so
   metadata is fully optional.
 
-### Additional requirements
+### The frozen VAE is included
 
-The frozen Flux.2 VAE is required to encode and decode latents and is not included here. Use the
-**Apache-2.0** copy that Black Forest Labs ships inside
-[`FLUX.2-klein-base-4B`](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4B) — only the
-autoencoder, not the transformer:
+`vae/` in this repository holds the frozen Flux.2 autoencoder that encodes and decodes the latents,
+so `snapshot_download` gives you everything the model needs:
 
 ```bash
-huggingface-cli download black-forest-labs/FLUX.2-klein-base-4B \
-    vae/diffusion_pytorch_model.safetensors --local-dir FLUX.2-klein-base-4B
+python inference.py --ckpt /path/to/GeoCore-9B --vae /path/to/GeoCore-9B/vae ...
 ```
 
-`models/vae_flux2.py` reads that file directly (`load_autoencoder`), so no conversion step is
-needed. CLIP and T5 text encoders are downloaded from the Hub at runtime.
+`models/vae_flux2.py` reads it directly (`load_autoencoder`), and `vae/config.json` is included so
+`diffusers >= 0.37` can load it too:
+
+```python
+from diffusers import AutoencoderKLFlux2
+vae = AutoencoderKLFlux2.from_pretrained("JeonghyeokDo/GeoCore-9B", subfolder="vae")
+```
+
+CLIP and T5 text encoders are still downloaded from the Hub at runtime.
 
 > [!IMPORTANT]
 > Do **not** substitute `ae.safetensors` from `FLUX.2-dev`. It holds the same autoencoder weights,
 > but under the FLUX Non-Commercial License v2.1, whose §4(a)(iii) forbids "surveillance purposes,
 > including all research and development related to surveillance" — a clause that Earth-observation
-> work should not have to argue about. The Klein-4B copy is Apache-2.0 and ungated, and the two were
+> work should not have to argue about. The copy shipped here is Apache-2.0, and the two were
 > verified identical by pairing every tensor on value: 250 of 251 pair one-to-one with a worst
 > deviation of 7.802e-03 (bf16 rounding); the odd one out is a BatchNorm step counter. In bf16, the
 > precision this model runs in, latents and reconstructions are bit-identical.
@@ -129,12 +134,31 @@ needed. CLIP and T5 text encoders are downloaded from the Hub at runtime.
 * Geospatial conditioning reflects correlations in the training corpus and is not a substitute for
   real observations of a location.
 
-## License
+## License and attribution
+
+GeoCore-9B is released under Apache-2.0, and so is every weight needed to run it.
+
+**`model-*.safetensors` (the 9.24B DiT)** — Copyright 2026 Jeonghyeok Do and Munchurl Kim,
+Apache-2.0. Trained from scratch on Git-10M; not derived from any FLUX checkpoint.
+
+**`vae/` (the frozen 84M autoencoder)** — Copyright Black Forest Labs, **Apache-2.0**. This is an
+**unmodified, byte-identical redistribution** of
+[`black-forest-labs/FLUX.2-klein-base-4B`](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4B)
+`vae/diffusion_pytorch_model.safetensors` and its `vae/config.json`, bundled here only so the model
+is usable in one download. Verify it against upstream:
+
+```
+sha256  ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04  vae/diffusion_pytorch_model.safetensors
+sha256  0d6dfb69ae95a5e2ac9836284bbb63d8b38ce67b25ba2dff380752b2a10ab948  vae/config.json
+```
+
+Those digests are the upstream files' own. A copy of the Apache License 2.0 as distributed with
+that model is included as [`LICENSE-FLUX2-VAE.md`](LICENSE-FLUX2-VAE.md). Black Forest Labs neither
+endorses nor is affiliated with GeoCore-9B; the attribution above is a statement of origin, not of
+sponsorship.
 
-GeoCore-9B is released under Apache-2.0, and so is every weight needed to run it: the DiT is trained
-from scratch on Git-10M and is not derived from any FLUX checkpoint, and the frozen VAE is taken
-from the Apache-2.0 Klein-4B release. Note that the [Git-10M](https://huggingface.co/datasets/lcybuaa/Git-10M)
-training corpus is CC BY-NC-ND 4.0, which restricts (re)training on that data to non-commercial use.
+The [Git-10M](https://huggingface.co/datasets/lcybuaa/Git-10M) training corpus is CC BY-NC-ND 4.0,
+which restricts (re)training on that data to non-commercial use.
 
 ## Citation
 

SHA256SUMS

@@ -4,3 +4,6 @@
 7cef9bd84c652cb25d0868d0f06d3cc4279d8a066db219f9c5f3fb4c7ac7288a  model-00004-of-00004.safetensors
 6af0afb014d208f28e04804cb0bbe8bdf3b52a8490cf3610e001b85c17fa8b65  model.safetensors.index.json
 5b289da77aa6062d83ddb87c81b450e452e75f488401329cabbc0890ee2805b3  config.json
+ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04  vae/diffusion_pytorch_model.safetensors
+0d6dfb69ae95a5e2ac9836284bbb63d8b38ce67b25ba2dff380752b2a10ab948  vae/config.json
+ca02bc51900ab07789d1b70283329e7137f5af98f5161c23a1c81fc38a4af1fe  LICENSE-FLUX2-VAE.md

vae/config.json

@@ -0,0 +1,40 @@
+{
+  "_class_name": "AutoencoderKLFlux2",
+  "_diffusers_version": "0.37.0.dev0",
+  "_name_or_path": "black-forest-labs/FLUX.2-dev",
+  "act_fn": "silu",
+  "batch_norm_eps": 0.0001,
+  "batch_norm_momentum": 0.1,
+  "block_out_channels": [
+    128,
+    256,
+    512,
+    512
+  ],
+  "down_block_types": [
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D"
+  ],
+  "force_upcast": true,
+  "in_channels": 3,
+  "latent_channels": 32,
+  "layers_per_block": 2,
+  "mid_block_add_attention": true,
+  "norm_num_groups": 32,
+  "out_channels": 3,
+  "patch_size": [
+    2,
+    2
+  ],
+  "sample_size": 1024,
+  "up_block_types": [
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D"
+  ],
+  "use_post_quant_conv": true,
+  "use_quant_conv": true
+}

vae/diffusion_pytorch_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04
+size 168120878