Instructions to use cxj009/lora_bumblebee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cxj009/lora_bumblebee with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/rev-anim", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("cxj009/lora_bumblebee") prompt = "<bumblebee>" image = pipe(prompt).images[0] - Transformers
How to use cxj009/lora_bumblebee with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cxj009/lora_bumblebee", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from cxj009/lora_bumblebee: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/cxj009/lora_bumblebee/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://cxj009/lora_bumblebee/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/cxj009/lora_bumblebee/resolve/main/checkpoint-500/optimizer.bin
6.59 MB
- Xet hash:
- 47f07a56b5ef95346e52650088eaf86e81226075502f28f5063b5b7281f3eefb
- Size of remote file:
- 6.59 MB
- SHA256:
- 1f9ddd98c5aaa352ee5bf763c23c634d7a2efd90a8e419926d4e4b250a159be5
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