Instructions to use KBlueLeaf/MOSS-Image-FP16-fixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KBlueLeaf/MOSS-Image-FP16-fixed with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KBlueLeaf/MOSS-Image-FP16-fixed", 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
Show plain fp16 going NaN at 2560x2560
Browse files- .gitattributes +1 -0
- images/base_fp16_break_2560.webp +3 -0
.gitattributes
CHANGED
|
@@ -157,3 +157,4 @@ images/sft_c_sweep_p0_0.webp filter=lfs diff=lfs merge=lfs -text
|
|
| 157 |
images/sft_c_sweep_p0_1.webp filter=lfs diff=lfs merge=lfs -text
|
| 158 |
images/sft_plain_fp16_p1.webp filter=lfs diff=lfs merge=lfs -text
|
| 159 |
images/sft_stream_per_block.webp filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 157 |
images/sft_c_sweep_p0_1.webp filter=lfs diff=lfs merge=lfs -text
|
| 158 |
images/sft_plain_fp16_p1.webp filter=lfs diff=lfs merge=lfs -text
|
| 159 |
images/sft_stream_per_block.webp filter=lfs diff=lfs merge=lfs -text
|
| 160 |
+
images/base_fp16_break_2560.webp filter=lfs diff=lfs merge=lfs -text
|
images/base_fp16_break_2560.webp
ADDED
|
Git LFS Details
|