Instructions to use Fascam/Atlas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Fascam/Atlas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Fascam/Atlas", 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
File size: 325 Bytes
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license: unknown
datasets:
- Congliu/Chinese-DeepSeek-R1-Distill-data-110k
- Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT
- allenai/olmOCR-mix-0225
- open-thoughts/OpenThoughts-114k
- fka/awesome-chatgpt-prompts
metrics:
- code_eval
- character
- accuracy
- cer
new_version: sesame/csm-1b
library_name: diffusers
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