Instructions to use shansuja/road_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use shansuja/road_classification with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("shansuja/road_classification") - Diffusers
How to use shansuja/road_classification with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tensor-diffusion/Ether-Blu-Mix-V5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("shansuja/road_classification") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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base_model: tensor-diffusion/Ether-Blu-Mix-V5
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instance_prompt: null
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license: apache-2.0
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---
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# sp_test1
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Weights for this model are available in PyTorch format.
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[Download](/shansuja/road_classification/tree/main) them in the Files & versions tab.
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base_model: tensor-diffusion/Ether-Blu-Mix-V5
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instance_prompt: null
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license: apache-2.0
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pipeline_tag: image-classification
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---
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# sp_test1
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Weights for this model are available in PyTorch format.
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[Download](/shansuja/road_classification/tree/main) them in the Files & versions tab.
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