Instructions to use casiatao/LRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use casiatao/LRM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("casiatao/LRM", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vqa_aes_clip_score_mp.csv from casiatao/LRM: direct link, hf CLI and curl.
- Browser
- Download file 71.8 MB
-
https://huggingface.co/casiatao/LRM/resolve/main/vqa_aes_clip_score_mp.csv
- Command line
-
hf download hf://casiatao/LRM/vqa_aes_clip_score_mp.csv
-
curl -L -o vqa_aes_clip_score_mp.csv https://huggingface.co/casiatao/LRM/resolve/main/vqa_aes_clip_score_mp.csv
71.8 MB
- Xet hash:
- 18960e478066c2d3ebfce145736076651d8d8437877eb72da41825d91a4d585b
- Size of remote file:
- 71.8 MB
- SHA256:
- e1096f5fca66e12c8f17b4b85f4239f36eab4e133c2b0b37eceec46bdc15d4d8
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