Instructions to use meoconxinhxan/emad_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use meoconxinhxan/emad_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("meoconxinhxan/emad_test") prompt = "<EMAD> running the inc that open source code, models and datasets powering & powered by AI money" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from meoconxinhxan/emad_test: direct link, hf CLI and curl.
- Browser
- Download file 315 MB
-
https://huggingface.co/meoconxinhxan/emad_test/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://meoconxinhxan/emad_test/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/meoconxinhxan/emad_test/resolve/main/checkpoint-500/optimizer.bin
315 MB
- Xet hash:
- b65e6375cf7d16a5461d2551fa1d62766168e124abf3f1c6bad607f4c105b0db
- Size of remote file:
- 315 MB
- SHA256:
- c124aca42b3c774ab50aa6140bc552d79f36870b9397dd9fbf0dfb9802078324
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