End of training

.gitattributes

@@ -36,3 +36,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 image_1.png filter=lfs diff=lfs merge=lfs -text
 image_2.png filter=lfs diff=lfs merge=lfs -text
 image_3.png filter=lfs diff=lfs merge=lfs -text
+image_0.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -9,28 +9,28 @@ tags:
 - template:sd-lora
 widget:
 
-        - text: 'a <s0><s1> emoji dressed as yoda'
+        - text: 'watercolor painting of a <s0><s1> woman with pink hair in New York'
           output:
             url:
                 "image_0.png"
         
-        - text: 'a <s0><s1> emoji dressed as yoda'
+        - text: 'watercolor painting of a <s0><s1> woman with pink hair in New York'
           output:
             url:
                 "image_1.png"
         
-        - text: 'a <s0><s1> emoji dressed as yoda'
+        - text: 'watercolor painting of a <s0><s1> woman with pink hair in New York'
           output:
             url:
                 "image_2.png"
         
-        - text: 'a <s0><s1> emoji dressed as yoda'
+        - text: 'watercolor painting of a <s0><s1> woman with pink hair in New York'
           output:
             url:
                 "image_3.png"
         
 base_model: stabilityai/stable-diffusion-xl-base-1.0
-instance_prompt: a <s0><s1> emoji
+instance_prompt: a <s0><s1> woman
 license: openrail++
 ---
 
@@ -51,7 +51,7 @@ license: openrail++
     - On AUTOMATIC1111, load the LoRA by adding `<lora:huggy_lora_v4:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
 - *Embeddings*: download **[`huggy_lora_v4_emb.safetensors` here 💾](/linoyts/huggy_lora_v4/blob/main/huggy_lora_v4_emb.safetensors)**.
     - Place it on it on your `embeddings` folder
-    - Use it by adding `huggy_lora_v4_emb` to your prompt. For example, `a huggy_lora_v4_emb emoji`
+    - Use it by adding `huggy_lora_v4_emb` to your prompt. For example, `a huggy_lora_v4_emb woman`
     (you need both the LoRA and the embeddings as they were trained together for this LoRA)
     
 
@@ -70,7 +70,7 @@ 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 <s0><s1> emoji dressed as yoda').images[0]
+image = pipeline('watercolor painting of a <s0><s1> woman with pink hair in New York').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)

huggy_lora_v4.safetensors

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 size 186046568

huggy_lora_v4_emb.safetensors

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-oid sha256:612cd8a8e8abb1e7019117783506217a83b7ae8ad922288bbbb7ad828cf20ad7
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 size 16536

pytorch_lora_weights.safetensors

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 size 185963768