Instructions to use mm9all/klein9b-lora-klein9b-lora-j9n8xs-9b-test-3-1770645277 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mm9all/klein9b-lora-klein9b-lora-j9n8xs-9b-test-3-1770645277 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-9B", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mm9all/klein9b-lora-klein9b-lora-j9n8xs-9b-test-3-1770645277") prompt = "a photo of AndyYang" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files- README.md +7 -0
- pytorch_lora_weights.safetensors +1 -1
- training_metadata.json +1 -1
- training_progress.json +1 -1
README.md
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- flux2-klein
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- template:sd-lora
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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- flux2-klein
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- flux2-klein-diffusers
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- template:sd-lora
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- diffusers-training
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- flux2-klein
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- template:sd-lora
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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pytorch_lora_weights.safetensors
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training_metadata.json
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"learning_rate": 0.0001,
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"lr_scheduler": "constant",
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"lr_warmup_steps": 20,
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"original_max_train_steps":
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"train_batch_size": 1,
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"gradient_accumulation_steps": 4,
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"checkpointing_steps": 50,
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"learning_rate": 0.0001,
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"lr_scheduler": "constant",
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"lr_warmup_steps": 20,
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"original_max_train_steps": 100,
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"train_batch_size": 1,
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"gradient_accumulation_steps": 4,
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"checkpointing_steps": 50,
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training_progress.json
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{"current_step":
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{"current_step": 0, "total_steps": 100, "resume_from_step": 0, "current_loss": 0.0, "best_loss": null, "best_checkpoint_step": null, "current_lr": 0.0, "step_time": 7.0, "eta_seconds": 700, "progress": 0, "status": "training", "model_version": "klein_9b"}
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