End of training

README.md

@@ -0,0 +1,75 @@
+---
+base_model:
+- krea/Krea-2-Turbo
+- krea/Krea-2-Raw
+library_name: diffusers
+license: apache-2.0
+instance_prompt: Manwha
+widget: []
+tags:
+- text-to-image
+- diffusers-training
+- diffusers
+- lora
+- krea2
+- krea2-diffusers
+- template:sd-lora
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# Krea 2 DreamBooth LoRA - Wonky468/silver
+
+<Gallery />
+
+## Model description
+
+These are Wonky468/silver DreamBooth LoRA weights, trained on krea/Krea-2-Raw.
+
+The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [Krea 2 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_krea2.md).
+
+Krea 2 ships as two checkpoints: **RAW** (the non-distilled base you fine-tune on) and **Turbo** (an 8-step distilled checkpoint for fast, high-quality inference). Train your LoRA on RAW and run it on Turbo — LoRAs trained on RAW express strongly on Turbo.
+
+## Trigger words
+
+You should use `Manwha` to trigger the image generation.
+
+## Download model
+
+[Download the *.safetensors LoRA](Wonky468/silver/tree/main) in the Files & versions tab.
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+>>> import torch
+>>> from diffusers import Krea2Pipeline
+
+>>> # Load the LoRA onto Krea 2 Turbo (the distilled inference model)
+>>> pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
+>>> pipe.load_lora_weights("Wonky468/silver")
+
+>>> # Turbo recipe: 8 steps, no classifier-free guidance
+>>> image = pipe("Manwha", num_inference_steps=8, guidance_scale=0.0).images[0]
+>>> image.save("output.png")
+```
+
+For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]

checkpoint-1000/optimizer.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dc7c5d1cb356979b452cd73996a018938ea966e8b8db149603bfc634ab6a4fcb
+size 195389021

checkpoint-1000/pytorch_lora_weights.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0dff056f4443b9cf76f9fcc2834c89285749788011377c376220bd0e53b460a2
+size 191879256

checkpoint-1000/random_states_0.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa48df2893b9c71a6873ae16cfac1d659f076444f3e2af8f873b3169edbdb7fd
+size 14757

checkpoint-1000/scheduler.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:95d5da8195335d4ea322bbf2d1a3e2e6db077cf77404469c5cb95a451f7e56fa
+size 1401

checkpoint-500/optimizer.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f03b94cbe60ff5c286245596b5ed9ac2798863717b656f0c9341e980c93f7716
+size 195389021

checkpoint-500/pytorch_lora_weights.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b37ee954dfd434b2fb5a944bcc2ab00c06a20b3e1865ad5b90354efc52508773
+size 191879256

checkpoint-500/random_states_0.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44ee722e1180c150a40bf249b1afa5c7cf791de96416681b86026ed6f516f17b
+size 14757

checkpoint-500/scheduler.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6b09a32f9bd8c3811caf53e7088f9d0094eade3af68c322a05eb696814b1a19
+size 1401

pytorch_lora_weights.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6693b2cb6952d6dfb60d923c7440deaf48be8a1b55ff7944a6ebe45d77186557
+size 191879256