End of training

.gitattributes

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README.md

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+---
+base_model: black-forest-labs/FLUX.1-dev
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- FLUX
+- FLUX-diffusers
+- text-to-image
+- diffusers
+- diffusers-training
+- textual_inversion
+inference: true
+---
+
+<!-- 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. -->
+
+
+# Textual inversion text2image fine-tuning - rangwani-harsh/logs
+These are textual inversion adaption weights for black-forest-labs/FLUX.1-dev. You can find some example images in the following. 
+
+![img_0](./image_0.png)
+![img_1](./image_1.png)
+![img_2](./image_2.png)
+![img_3](./image_3.png)
+
+
+
+## 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]

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+  "_diffusers_version": "0.30.3",
+  "_name_or_path": "black-forest-labs/FLUX.1-dev",
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
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+  ],
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+    "FluxTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

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+  "_diffusers_version": "0.30.3",
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+  "base_shift": 0.5,
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+  "max_shift": 1.15,
+  "num_train_timesteps": 1000,
+  "shift": 3.0,
+  "use_dynamic_shifting": true
+}

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+  "num_hidden_layers": 12,
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+  "projection_dim": 768,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.1",
+  "vocab_size": 49409
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