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
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Download README.md from Fascam/Atlas: direct link, hf CLI and curl.
- Browser
- Download file 325 Bytes
-
https://huggingface.co/Fascam/Atlas/resolve/main/README.md
- Command line
-
hf download hf://Fascam/Atlas/README.md
-
curl -L -o README.md https://huggingface.co/Fascam/Atlas/resolve/main/README.md
325 Bytes
metadata
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