Instructions to use ShreyashDhoot/v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShreyashDhoot/v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ShreyashDhoot/v3") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Upload folder using huggingface_hub
Browse files
checkpoints/checkpoint--2500/adapter_config.json
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha":
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"lora_bias": false,
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"lora_dropout": 0.
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"target_parameters": null,
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"task_type": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 128,
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"lora_bias": false,
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"lora_dropout": 0.01,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r": 128,
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"rank_pattern": {},
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"revision": null,
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"to_k",
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"to_v",
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"to_out.0",
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"ff.net.2",
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"ff.net.0.proj",
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"to_q"
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"target_parameters": null,
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"task_type": null,
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checkpoints/checkpoint--2500/adapter_model.safetensors
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