Instructions to use ByteDance/Bernini-Diffusers-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/Bernini-Diffusers-v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/Bernini-Diffusers-v2", 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
Download mllm/generation_config.json from ByteDance/Bernini-Diffusers-v2: direct link, hf CLI and curl.
- Browser
- Download file 216 Bytes
-
https://huggingface.co/ByteDance/Bernini-Diffusers-v2/resolve/main/mllm/generation_config.json
- Command line
-
hf download hf://ByteDance/Bernini-Diffusers-v2/mllm/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/ByteDance/Bernini-Diffusers-v2/resolve/main/mllm/generation_config.json
216 Bytes
| { | |
| "bos_token_id": 151643, | |
| "pad_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "repetition_penalty": 1.05, | |
| "temperature": 0.000001, | |
| "transformers_version": "4.37.0" | |
| } |