Instructions to use Mark000111888/llv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mark000111888/llv2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mark000111888/llv2", 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 text_encoder/pytorch_model.bin from Mark000111888/llv2: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Mark000111888/llv2/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Mark000111888/llv2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mark000111888/llv2/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 5bd34c6fa797f3776c61638b6a60aa25fc2677a9a2c3bc48f2035555a7940840
- Size of remote file:
- 492 MB
- SHA256:
- 539f7f2bd312ea18c64621e1ce6684e635eab6a1adda00f5e2c12aa39b407a0b
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