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-200/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-200/optimizer.bin
- Command line
-
hf download hf://cxj009/lora_bumblebee/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/cxj009/lora_bumblebee/resolve/main/checkpoint-200/optimizer.bin
6.59 MB
- Xet hash:
- 801c66d2895f6f520af47add91366f74ff0885e1e766a4f2f607cfe13d36787b
- Size of remote file:
- 6.59 MB
- SHA256:
- 099bc0d63bb964787387acf6ffdefcb2188f364da58e1a63a29b50374efa58d0
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