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README.md

@@ -1,38 +1,46 @@
 ---
+license: other
+license_name: flux-1-dev-non-commercial-license
+license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
+language:
+- en
 tags:
-- text-to-image
-- lora
+- flux
 - diffusers
-- template:diffusion-lora
-widget:
-- text: portrait of José Alves with black suit in gray blurred background
-  output:
-    url: images/jalves.jpeg
-base_model: black-forest-labs/FLUX.1-dev
-instance_prompt: José Alves, Pedro, Júlio, Clóvis
-license: mit
+- lora
+- replicate
+base_model: "black-forest-labs/FLUX.1-dev"
+pipeline_tag: text-to-image
+# widget:
+#   - text: >-
+#       prompt
+#     output:
+#       url: https://...
+instance_prompt: Júlio
 ---
-# Jalves
-
-<Gallery />
 
-## Model description 
+# Uniodonto
 
-Inferências dos Diretores da Uniodonto do Brasil
+<Gallery />
 
-## Trigger words
+Trained on Replicate using:
 
-You should use `José Alves` to trigger the image generation.
+https://replicate.com/ostris/flux-dev-lora-trainer/train
 
-You should use `Pedro` to trigger the image generation.
 
+## Trigger words
 You should use `Júlio` to trigger the image generation.
 
-You should use `Clóvis` to trigger the image generation.
 
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
 
-## Download model
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
 
-Weights for this model are available in Safetensors format.
+pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('Collos/uniodonto', weight_name='lora.safetensors')
+image = pipeline('your prompt').images[0]
+```
 
-[Download](/Collos/uniodonto/tree/main) them in the Files & versions tab.
+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)

config.yaml

@@ -5,14 +5,14 @@ config:
   - type: custom_sd_trainer
     training_folder: output
     device: cuda:0
-    trigger_word: "Jos\xE9 Alves"
+    trigger_word: "J\xFAlio"
     network:
       type: lora
       linear: 16
       linear_alpha: 16
     save:
       dtype: float16
-      save_every: 2001
+      save_every: 3001
       max_step_saves_to_keep: 1
     datasets:
     - folder_path: input_images
@@ -25,7 +25,7 @@ config:
       - 1024
     train:
       batch_size: 1
-      steps: 2000
+      steps: 3000
       gradient_accumulation_steps: 1
       train_unet: true
       train_text_encoder: false
@@ -44,7 +44,7 @@ config:
       quantize: true
     sample:
       sampler: flowmatch
-      sample_every: 2001
+      sample_every: 3001
       width: 1024
       height: 1024
       prompts: []

lora.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3fccd46ee885df9b2712bb84798147edfd77c53706db20cbb80cc34221eb1653
-size 171969440
+oid sha256:c948b98d3385509bf8bc2e75c81bfea7a24f05fa0d86ccefa2b86c9e9ec13935
+size 171969432