Upload 85 files

.gitattributes

@@ -33,3 +33,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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flux2.peft-lora+TREAD/all_image_files_emi-1024.json

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flux2.peft-lora+TREAD/all_image_files_emi-1440.json

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flux2.peft-lora+TREAD/all_image_files_emi-256.json

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flux2.peft-lora+TREAD/all_image_files_emi-512.json

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flux2.peft-lora+TREAD/all_image_files_emi-768.json

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flux2.peft-lora+TREAD/all_image_files_emi-crop-1024.json

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flux2.peft-lora+TREAD/all_image_files_emi-crop-1440.json

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flux2.peft-lora+TREAD/all_image_files_emi-crop-256.json

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flux2.peft-lora+TREAD/all_image_files_emi-crop-512.json

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flux2.peft-lora+TREAD/all_image_files_emi-crop-768.json

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flux2.peft-lora+TREAD/all_text_cache_files_text-embed-cache.json

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flux2.peft-lora+TREAD/all_vae_cache_files_emi-1440.json

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flux2.peft-lora+TREAD/checkpoint-2100/training_state.json

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flux2.peft-lora+TREAD/checkpoint-2400/README.md

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+---
+license: other
+base_model: "black-forest-labs/FLUX.2-dev"
+tags:
+  - flux2
+  - flux2-diffusers
+  - text-to-image
+  - image-to-image
+  - diffusers
+  - simpletuner
+  - safe-for-work
+  - lora
+
+  - template:sd-lora
+  - standard
+pipeline_tag: text-to-image
+inference: true
+
+---
+
+# quzo/textf23
+
+This is a PEFT LoRA derived from [black-forest-labs/FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev).
+
+The main validation prompt used during training was:
+```
+quz0 man is holding a sign that says hello world from flux2
+```
+
+
+## Validation settings
+- CFG: `4.0`
+- CFG Rescale: `0.0`
+- Steps: `16`
+- Sampler: `FlowMatchEulerDiscreteScheduler`
+- Seed: `42`
+- Resolution: `1024x1024`
+
+
+Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
+
+
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 4
+- Training steps: 2400
+- Learning rate: 0.0001
+  - Learning rate schedule: constant
+  - Warmup steps: 0
+- Max grad value: 2.0
+- Effective batch size: 2
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 2
+  - Number of GPUs: 1
+- Gradient checkpointing: True
+- Prediction type: flow_matching[]
+- Optimizer: adamw_bf16
+- Trainable parameter precision: Pure BF16
+- Base model precision: `no_change`
+- Caption dropout probability: 0.1%
+
+
+
+- LoRA Rank: 32
+- LoRA Alpha: 32.0
+- LoRA Dropout: 0.1
+- LoRA initialisation style: default
+- LoRA mode: Standard
+    
+
+## Datasets
+
+### emi-256
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.065536 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+### emi-crop-256
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.065536 megapixels
+- Cropped: True
+- Crop style: center
+- Crop aspect: square
+- Used for regularisation data: No
+### emi-512
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.262144 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+### emi-crop-512
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.262144 megapixels
+- Cropped: True
+- Crop style: center
+- Crop aspect: square
+- Used for regularisation data: No
+### emi-768
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.589824 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+### emi-crop-768
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 0.589824 megapixels
+- Cropped: True
+- Crop style: center
+- Crop aspect: square
+- Used for regularisation data: No
+### emi-1024
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+### emi-crop-1024
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 1.048576 megapixels
+- Cropped: True
+- Crop style: center
+- Crop aspect: square
+- Used for regularisation data: No
+### emi-1440
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 3
+- Resolution: 2.0736 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+### emi-crop-1440
+- Repeats: 10
+- Total number of images: 10
+- Total number of aspect buckets: 2
+- Resolution: 2.0736 megapixels
+- Cropped: True
+- Crop style: center
+- Crop aspect: square
+- Used for regularisation data: No
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+
+model_id = 'black-forest-labs/FLUX.2-dev'
+adapter_id = 'quzo/quzo/textf23'
+pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
+pipeline.load_lora_weights(adapter_id)
+
+prompt = "quz0 man is holding a sign that says hello world from flux2"
+negative_prompt = 'ugly, cropped, blurry, low-quality, mediocre average'
+
+## Optional: quantise the model to save on vram.
+## Note: The model was not quantised during training, so it is not necessary to quantise it during inference time.
+#from optimum.quanto import quantize, freeze, qint8
+#quantize(pipeline.transformer, weights=qint8)
+#freeze(pipeline.transformer)
+    
+pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
+model_output = pipeline(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_inference_steps=16,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
+    width=1024,
+    height=1024,
+    guidance_scale=4.0,
+).images[0]
+
+model_output.save("output.png", format="PNG")
+
+```
+
+
+

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+    "huber_c": 0.1,
+    "snr_gamma": null,
+    "masked_loss_probability": 1.0,
+    "hidream_use_load_balancing_loss": false,
+    "hidream_load_balancing_loss_weight": null,
+    "adam_beta1": 0.9,
+    "adam_beta2": 0.999,
+    "optimizer_beta1": null,
+    "optimizer_beta2": null,
+    "optimizer_cpu_offload_method": null,
+    "gradient_precision": null,
+    "adam_weight_decay": 0.01,
+    "adam_epsilon": 1e-08,
+    "prodigy_steps": null,
+    "max_grad_norm": 2.0,
+    "optimizer_config": null,
+    "grad_clip_method": "value",
+    "optimizer_offload_gradients": false,
+    "fuse_optimizer": false,
+    "optimizer_release_gradients": false,
+    "push_to_hub": true,
+    "publishing_config": null,
+    "post_checkpoint_script": null,
+    "post_upload_script": null,
+    "push_checkpoints_to_hub": true,
+    "push_to_hub_background": true,
+    "hub_model_id": "quzo/textf23",
+    "model_card_private": false,
+    "model_card_safe_for_work": true,
+    "model_card_note": null,
+    "report_to": "none",
+    "custom_tracker": null,
+    "checkpoint_step_interval": 300,
+    "checkpoint_epoch_interval": null,
+    "checkpointing_rolling_steps": 0,
+    "checkpointing_use_tempdir": false,
+    "checkpoints_rolling_total_limit": 1,
+    "tracker_run_name": "example-training-run",
+    "tracker_project_name": "lora-training",
+    "tracker_image_layout": "gallery",
+    "enable_watermark": false,
+    "framerate": null,
+    "seed_for_each_device": true,
+    "snr_weight": 1.0,
+    "webhook_config": [
+        {
+            "webhook_type": "raw",
+            "callback_url": "http://0.0.0.0:8001/callback",
+            "log_level": "info",
+            "ssl_no_verify": false
+        }
+    ],
+    "webhook_reporting_interval": null,
+    "distillation_method": null,
+    "distillation_config": null,
+    "ema_validation": "comparison",
+    "local_rank": -1,
+    "ltx_train_mode": "i2v",
+    "ltx_i2v_prob": 0.1,
+    "ltx_partial_noise_fraction": 0.05,
+    "ltx_protect_first_frame": false,
+    "offload_param_path": null,
+    "offset_noise": false,
+    "quantize_activations": false,
+    "refiner_training": false,
+    "refiner_training_invert_schedule": false,
+    "refiner_training_strength": 0.2,
+    "sdxl_refiner_uses_full_range": false,
+    "sana_complex_human_instruction": "Given a user prompt, generate an 'Enhanced prompt' that provides detailed visual descriptions suitable for image generation. Evaluate the level of detail in the user prompt:\n- If the prompt is simple, focus on adding specifics about colors, shapes, sizes, textures, and spatial relationships to create vivid and concrete scenes.\n- Do not add detail that is not in the original prompt! Do not mention colors if the User Prompt does not!\n- If the prompt is already detailed, refine and enhance the existing details slightly without overcomplicating.\n- If the prompt contains explicit material, do not remove this information from the output, which would damage the performance of downstream classifiers.\nHere are examples of how to transform or refine prompts:\n- User Prompt: A cat sleeping -> Enhanced: A cat sleeping peacefully, showcasing the joy of pet ownership. Cute floof kitty cat gatto.\n- User Prompt: A busy city street -> Enhanced: A bustling city street scene featuring a crowd of people.\nPlease generate only the enhanced description for the prompt below and avoid including any additional commentary or evaluations:\nUser Prompt: ",
+    "vae_path": "black-forest-labs/FLUX.2-dev",
+    "accelerator_project_config": {
+        "project_dir": "/home/Ubuntu/.simpletuner/output/examples/flux2.peft-lora+TREAD",
+        "logging_dir": "/home/Ubuntu/.simpletuner/output/examples/flux2.peft-lora+TREAD/logs",
+        "automatic_checkpoint_naming": false,
+        "total_limit": null,
+        "iteration": 8,
+        "save_on_each_node": false
+    },
+    "process_group_kwargs": {
+        "backend": "nccl",
+        "init_method": null,
+        "timeout": "1:30:00"
+    },
+    "is_quantized": false,
+    "weight_dtype": "torch.bfloat16",
+    "disable_accelerator": false,
+    "lora_initialisation_style": true,
+    "checkpointing_steps": 300,
+    "use_fsdp": false,
+    "model_type_label": "Flux.2",
+    "use_deepspeed_optimizer": false,
+    "use_deepspeed_scheduler": false,
+    "base_weight_dtype": "torch.bfloat16",
+    "is_quanto": false,
+    "is_torchao": false,
+    "is_bnb": false,
+    "flow_matching": true,
+    "overrode_max_train_steps": false,
+    "total_num_batches": 1100,
+    "num_update_steps_per_epoch": 550,
+    "total_batch_size": 2,
+    "enable_adamw_bf16": true,
+    "is_schedulefree": false,
+    "is_lr_scheduler_disabled": false,
+    "total_steps_remaining_at_start": 4200
+}

flux2.peft-lora+TREAD/checkpoint-2400/training_state-emi-1024.json

@@ -0,0 +1 @@
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