End of training

README.md

@@ -8,28 +8,28 @@ tags:
 - template:sd-lora
 widget:
 
-        - text: 'a photo of <s0><s1>'
+        - text: 'a photo of <s0><s1> sad mummy, surrounded by fire'
           output:
             url:
                 "image_0.png"
         
-        - text: 'a photo of <s0><s1>'
+        - text: 'a photo of <s0><s1> sad mummy, surrounded by fire'
           output:
             url:
                 "image_1.png"
         
-        - text: 'a photo of <s0><s1>'
+        - text: 'a photo of <s0><s1> sad mummy, surrounded by fire'
           output:
             url:
                 "image_2.png"
         
-        - text: 'a photo of <s0><s1>'
+        - text: 'a photo of <s0><s1> sad mummy, surrounded by fire'
           output:
             url:
                 "image_3.png"
         
 base_model: stabilityai/stable-diffusion-xl-base-1.0
-instance_prompt: a photo of <s0><s1>
+instance_prompt: a photo of <s0><s1> sad mummy
 license: openrail++
 ---
 
@@ -50,7 +50,7 @@ license: openrail++
     - On AUTOMATIC1111, load the LoRA by adding `<lora:amumu-sdxl-lora:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
 - *Embeddings*: download **[`amumu-sdxl-lora_emb.safetensors` here 💾](/salma-remyx/amumu-sdxl-lora/blob/main/amumu-sdxl-lora_emb.safetensors)**.
     - Place it on it on your `embeddings` folder
-    - Use it by adding `amumu-sdxl-lora_emb` to your prompt. For example, `a photo of amumu-sdxl-lora_emb`
+    - Use it by adding `amumu-sdxl-lora_emb` to your prompt. For example, `a photo of amumu-sdxl-lora_emb sad mummy`
     (you need both the LoRA and the embeddings as they were trained together for this LoRA)
     
 
@@ -69,7 +69,7 @@ state_dict = load_file(embedding_path)
 pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
 pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
         
-image = pipeline('a photo of <s0><s1>').images[0]
+image = pipeline('a photo of <s0><s1> sad mummy, surrounded by fire').images[0]
 ```
 
 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)

amumu-sdxl-lora.safetensors

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pytorch_lora_weights.safetensors

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