Add merged Krea-2 turbo transformer (epoch-2-step-10455 (raw))
Browse files- epoch-2-step-10455/transformer/README.md +37 -0
- epoch-2-step-10455/transformer/config.json +25 -0
- epoch-2-step-10455/transformer/diffusion_pytorch_model-00001-of-00003.safetensors +3 -0
- epoch-2-step-10455/transformer/diffusion_pytorch_model-00002-of-00003.safetensors +3 -0
- epoch-2-step-10455/transformer/diffusion_pytorch_model-00003-of-00003.safetensors +3 -0
- epoch-2-step-10455/transformer/diffusion_pytorch_model.safetensors.index.json +437 -0
epoch-2-step-10455/transformer/README.md
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---
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library_name: diffusers
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base_model: krea/Krea-2-Raw
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tags:
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- text-to-image
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- krea2
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- distilled
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---
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# jimmycarter/krea2-turbo-bbox
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Merged **turbo (few-step distilled) transformer** for a Krea-2 finetune. Built as
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`turbo_epoch = epoch_checkpoint + (krea/Krea-2-Turbo - krea/Krea-2-Raw)` — the finetune's epoch
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weights carry the base→turbo distillation delta so they can be sampled in 8 steps, CFG-free.
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Variant: **epoch-1-step-5228 (raw)**.
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This is a **transformer-only** repo (everything else — VAE, text encoder, tokenizer, scheduler — is
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identical to `krea/Krea-2-Raw`). Load it as the transformer of a stock Krea-2 pipeline:
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```python
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import torch
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from diffusers import Krea2Pipeline, Krea2Transformer2DModel
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tf = Krea2Transformer2DModel.from_pretrained("jimmycarter/krea2-turbo-bbox", torch_dtype=torch.bfloat16)
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pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Raw", transformer=tf, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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# These are DISTILLED weights — sample at turbo settings:
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image = pipe("a photo of a cat", num_inference_steps=8, guidance_scale=0.0).images[0]
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image.save("out.png")
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```
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> **Note:** `is_distilled` is a pipeline-level flag (`model_index.json`), not a transformer config
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> field, so it can't be baked into this transformer-only upload. The pipeline above uses the fixed
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> distilled timestep shift (`mu=1.15`) when it treats the checkpoint as distilled; if your pipeline
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> build doesn't infer that, pass `mu=1.15` / set `is_distilled=True` explicitly.
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epoch-2-step-10455/transformer/config.json
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{
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"_class_name": "Krea2Transformer2DModel",
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"_diffusers_version": "0.39.0.dev0",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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32,
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48,
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48
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],
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"in_channels": 64,
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"intermediate_size": 16384,
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"norm_eps": 1e-05,
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"num_attention_heads": 48,
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"num_key_value_heads": 12,
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"num_layers": 28,
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"num_layerwise_text_blocks": 2,
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"num_refiner_text_blocks": 2,
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"num_text_layers": 12,
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"rope_theta": 1000.0,
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"text_hidden_dim": 2560,
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"text_intermediate_size": 6912,
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"text_num_attention_heads": 20,
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"text_num_key_value_heads": 20,
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"timestep_embed_dim": 256
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}
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epoch-2-step-10455/transformer/diffusion_pytorch_model-00001-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a92166547670fdd333a8d4a52d4afd98b90418fd51569abf3348df93a0301f5f
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size 9808262504
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epoch-2-step-10455/transformer/diffusion_pytorch_model-00002-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b0704a0c700ccd60027aad27184e8bd898aa51e28b38d21bf4312ab7e270780
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size 9941703832
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epoch-2-step-10455/transformer/diffusion_pytorch_model-00003-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:15619091b122f4d2ea4aa75a8299f50f85c505646bcdd120f58448bba5ac9628
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size 5890228944
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epoch-2-step-10455/transformer/diffusion_pytorch_model.safetensors.index.json
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{
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"metadata": {
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"total_size": 25640146072
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},
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| 5 |
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"weight_map": {
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"final_layer.linear.bias": "diffusion_pytorch_model-00003-of-00003.safetensors",
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"img_in.bias": "diffusion_pytorch_model-00001-of-00003.safetensors",
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"img_in.weight": "diffusion_pytorch_model-00001-of-00003.safetensors",
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"text_fusion.layerwise_blocks.0.attn.to_gate.weight": "diffusion_pytorch_model-00001-of-00003.safetensors",
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"text_fusion.layerwise_blocks.0.attn.to_k.weight": "diffusion_pytorch_model-00001-of-00003.safetensors",
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"text_fusion.layerwise_blocks.0.attn.to_out.0.weight": "diffusion_pytorch_model-00001-of-00003.safetensors",
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