The latent upscaler (radiance 1.8.1): card, licences, recipe

LICENSE-latent-upscaler

@@ -0,0 +1,202 @@
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NOTICE

@@ -10,3 +10,8 @@ repacked into one .rad container. minimax-h3-fp8.recipe lists the rules applied.
 
 The text encoder is Qwen3-VL-32B, licensed under the Apache License 2.0; a copy
 is included as LICENSE-Qwen3-VL. Source: https://github.com/QwenLM/Qwen3-VL
+
+The latent upscaler is Minimax_h3_latent_Upscaler v1 by LBH-123-AI
+(https://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler), licensed under
+the Apache License 2.0; a copy is included as LICENSE-latent-upscaler. Its
+weights are included as published (bf16), its embedding MLP cast to f32.

README.md

@@ -13,8 +13,10 @@ tags:
 - text-to-video
 - text-to-audio-video
 - minimax-h3
+- latent-upscaler
 base_model:
 - MiniMaxAI/MiniMax-H3
+- LBH-123-AI/Minimax_h3_latent_Upscaler
 ---
 
 # MiniMax-H3, FP8 — radiance container
@@ -28,10 +30,11 @@ Republic of Korea or the United States of America; see [License](#license).
 
 | | |
 |---|---|
-| File | `minimax-h3-fp8.rad` — 59.89 GiB |
+| File | `minimax-h3-fp8.rad` — 60.54 GiB |
 | Weights | every linear of the text encoder (the 50 layers of Qwen3-VL-32B the model reads), the token refiner and the DiT's 50 blocks, and the modulation projections, FP8 E4M3 per 128×128 block (bf16 scales); the video decoder bf16; the audio decoder f32 |
+| Latent upscaler | [LBH-123-AI/Minimax_h3_latent_Upscaler](https://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler) v1 (3D conv, 345M parameters, bf16; Apache-2.0) |
 | Output | MP4: H.264 at 24 fps, up to 1344x768, 5.17 to 14.4 s; AAC at 32 kHz stereo |
-| Needs | radiance 1.8.0 or newer (MiniMax-H3 support comes with 1.8.0); two 32 GB cards and about 39 GiB of pinned host memory |
+| Needs | radiance 1.8.1 or newer (the upscaler, and prompts over 128 tokens, need 1.8.1); two 32 GB cards and about 39 GiB of pinned host memory |
 
 ## Serve
 
@@ -67,6 +70,27 @@ from diffusers' bf16 pipeline, about what the reference itself moves with its li
 the same way (6.8% and 4.6%). Given the same latents, the video decoder is 36.9 dB PSNR from the
 reference's (H.264 included) and the audio decoder 51.0 dB SNR.
 
+## Latent upscaling
+
+The container carries LBH-123-AI's latent upscaler. A request with `"latent_upscale": 2` runs its
+first steps at half the size (672x384 for 1344x768), the upscaler enlarges the clean latent, and the
+last `upscale_refine_steps` (12 by default) run at the full size from a re-noised copy of it:
+
+```sh
+curl -s http://localhost:8000/v1/videos -H 'Content-Type: application/json' -d '{
+  "prompt": "...", "seconds": "5", "size": "1344x768", "seed": 7, "latent_upscale": 2}'
+```
+
+| 5.17 s at 1344x768, 50 steps, 2x R9700 | time |
+|---|---|
+| native | 8.8 min |
+| `latent_upscale` 2, 12 refine steps (the default) | 3.4 min |
+| `latent_upscale` 2, 20 refine steps | 4.5 min |
+
+The factor goes up to 4, but at 1344x768 a factor of 4 starts from 352x192, which is too small for
+the model to lay out a clean scene: expect soft, ghosted frames. The video object of an upscaled
+video reports `latent_upscale`, `upscale_refine_steps` and `upscale_from` (the small size).
+
 ## How this file was made
 
 ```sh
@@ -75,7 +99,11 @@ rad-convert MiniMaxAI/MiniMax-H3 --recipe minimax-h3-fp8.recipe -o minimax-h3-fp
 
 `MiniMaxAI/MiniMax-H3` is the downloaded pipeline directory; only its text-to-video-and-audio
 components are read (`text_encoder/`, `transformer/`, `vae/`, `audio_vae/`, the processor, the
-tokenizer and both schedulers). The recipe (`minimax-h3-fp8.recipe` in this repository) names what is
+tokenizer and both schedulers), and the upscaler as a companion folder `latent_upscaler/` (its
+`minimax_h3_latent_upscaler_3d_conv_v1/config.json` and bf16 weights, renamed
+`diffusion_pytorch_model.safetensors`). This file had it added to the 1.8.0 container in place
+(`rad-convert ... --reuse minimax-h3-fp8.rad --in-place`), which leaves every other weight as it
+was. The recipe (`minimax-h3-fp8.recipe` in this repository) names what is
 quantised; everything it does not name is the checkpoint's own dtype:
 
 ```
@@ -100,6 +128,8 @@ vae.blk.*.ffn_up.weight              cast dtype=bf16
 vae.blk.*.ffn_down.weight            cast dtype=bf16
 vae.proj_out.*                       cast dtype=bf16
 aud.*.weight                         cast dtype=f32
+ups.embed.*                          cast dtype=f32
+ups.*.emb_layers.*                   cast dtype=f32
 ```
 
 ## License
@@ -115,4 +145,6 @@ This container is a modified copy of MiniMax H3: the linears named above are re-
 video decoder's linears cast from f32 to bf16, the audio decoder's weight norms folded, the text
 encoder's last 14 layers (which the model does not read) left out, and everything repacked into one
 `.rad` file. The text encoder is Qwen3-VL-32B, licensed under the Apache License 2.0
-(`LICENSE-Qwen3-VL`).
+(`LICENSE-Qwen3-VL`). The latent upscaler is LBH-123-AI's Minimax_h3_latent_Upscaler v1, licensed
+under the Apache License 2.0 (`LICENSE-latent-upscaler`); its weights are included as published,
+its embedding MLP cast from bf16 to f32.

minimax-h3-fp8.recipe

@@ -15,6 +15,15 @@
 #       --reuse minimax-h3-fp8.rad --changed <the transformer's tensor names, "transformer." first> \
 #       -o fasth3-8step-fp8.rad
 #
+# LBH-123-AI's latent upscaler (Minimax_h3_latent_Upscaler, Apache-2.0) is a companion folder:
+# put its config.json (minimax_h3_latent_upscaler_3d_conv_v1/config.json) and its bf16 weights,
+# named diffusion_pytorch_model.safetensors, in latent_upscaler/ of the pipeline directory. It
+# converts with the rest, or is appended to a container converted without it, which keeps every
+# weight the container holds where it is:
+#
+#   rad-convert <pipeline directory> --recipe data/recipes/minimax-h3-fp8.recipe \
+#       --reuse minimax-h3-fp8.rad --in-place
+#
 # Every linear of the text encoder's first 50 layers, of the token refiner and of the DiT's 50
 # blocks, and the per-modality modulation projections, become E4M3 codes with a bf16 scale a
 # 128 x 128 block, read by the fp8a8 GEMMs. What keeps the checkpoint's precision is read once a
@@ -44,3 +53,5 @@ vae.blk.*.ffn_up.weight              cast dtype=bf16
 vae.blk.*.ffn_down.weight            cast dtype=bf16
 vae.proj_out.*                       cast dtype=bf16
 aud.*.weight                         cast dtype=f32
+ups.embed.*                          cast dtype=f32
+ups.*.emb_layers.*                   cast dtype=f32