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
Upload training_metadata.json with huggingface_hub
Browse files- training_metadata.json +2 -2
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":
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"num_images": 8
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}
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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": 1100,
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"train_batch_size": 1,
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"gradient_accumulation_steps": 4,
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"checkpointing_steps": 100,
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"num_images": 8
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}
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