cookey39
/

reflector

@@ -1,198 +1,68 @@
----
-library_name: diffusers
----
-# Model Card for Model ID
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+# SDXL LoRA DreamBooth - cookey39/reflector
+### Examples:
+https://www.pixiv.net/artworks/119270564
+https://www.pixiv.net/artworks/119269797
+<Gallery />
+## Model description
+### These are cookey39/reflector LoRA adaption weights for cookey39/hyper-sd-8step.
+## Download model
+### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
+- **LoRA**: download **[`reflector.safetensors` here 💾](/cookey39/reflector/blob/main/reflector.safetensors)**.
+    - Place it on your `models/Lora` folder.
+    - On AUTOMATIC1111, load the LoRA by adding `<lora:reflector:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
+- *Embeddings*: download **[`reflector_emb.safetensors` here 💾](/cookey39/reflector/blob/main/reflector_emb.safetensors)**.
+    - Place it on it on your `embeddings` folder
+    - Use it by adding `reflector_emb` to your prompt. For example, `blue_reflection:`
+    (you need both the LoRA and the embeddings as they were trained together for this LoRA)
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+```py
+from diffusers import AutoPipelineForText2Image
+from diffusers import DiffusionPipeline, DDIMScheduler
+import torch
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+pipeline = AutoPipelineForText2Image.from_pretrained('cookey39/reflector', torch_dtype=torch.float16).to('cuda')
+# lower eta results in more detail
+instance_token = "<s0><s1>"
+prompt = f"a {instance_token}masterpiece, best quality,long hair, cute face, white kneehighs, black hair, hair strand, twin braids, cat hair ornament, adorable girl, absurdres, huge_filesize, Japanese, game_cg, {instance_token}  "
+negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet, "
+image = pipeline(prompt=prompt, negative_prompt = negative_prompt, num_inference_steps=50, cross_attention_kwargs={"scale": 1.0},width = 720, height=1080).images[0]
+image
+```
+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)
+## Trigger words
+To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
+to trigger concept `TOK` → use `<s0><s1>` in your prompt
+## Details
+All [Files & versions](/cookey39/reflector/tree/main).
+The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).
+LoRA for the text encoder was enabled. False.
+Pivotal tuning was enabled: True.
+Special VAE used for training: None.