Instructions to use ngoctham/Lens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ngoctham/Lens with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ngoctham/Lens", 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/generation_config.json from ngoctham/Lens: direct link, hf CLI and curl.
- Browser
- Download file 171 Bytes
-
https://huggingface.co/ngoctham/Lens/resolve/main/text_encoder/generation_config.json
- Command line
-
hf download hf://ngoctham/Lens/text_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/ngoctham/Lens/resolve/main/text_encoder/generation_config.json
171 Bytes
| { | |
| "bos_token_id": 199998, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 200002, | |
| 199999, | |
| 200012 | |
| ], | |
| "pad_token_id": 199999, | |
| "transformers_version": "5.8.0" | |
| } | |