Instructions to use anupamtripathi/model_sd2_new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anupamtripathi/model_sd2_new_data with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("anupamtripathi/model_sd2_new_data") prompt = "a photo of Beavertail Pastry food products" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-300/optimizer.bin from anupamtripathi/model_sd2_new_data: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/anupamtripathi/model_sd2_new_data/resolve/main/checkpoint-300/optimizer.bin
- Command line
-
hf download hf://anupamtripathi/model_sd2_new_data/checkpoint-300/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/anupamtripathi/model_sd2_new_data/resolve/main/checkpoint-300/optimizer.bin
6.85 MB
- Xet hash:
- 712f98e80f8f0fe37e22f8b6fb56827f53bc6e3de8c6e4d83d3b50574d6bb80e
- Size of remote file:
- 6.85 MB
- SHA256:
- e44e08a4777cbd2b535765410e2af61cf9713e4ea460ea04b50c130aa4e8e441
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