Instructions to use BLIP3o/BLIP3o-Model-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BLIP3o/BLIP3o-Model-8B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BLIP3o/BLIP3o-Model-8B", 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 diffusion-decoder/model_index.json from BLIP3o/BLIP3o-Model-8B: direct link, hf CLI and curl.
- Browser
- Download file 607 Bytes
-
https://huggingface.co/BLIP3o/BLIP3o-Model-8B/resolve/refs%2Fpr%2F3/diffusion-decoder/model_index.json
- Command line
-
hf download hf://BLIP3o/BLIP3o-Model-8B@refs/pr/3/diffusion-decoder/model_index.json
-
curl -L -o model_index.json https://huggingface.co/BLIP3o/BLIP3o-Model-8B/resolve/refs%2Fpr%2F3/diffusion-decoder/model_index.json
607 Bytes
| { | |
| "_class_name": "EmuVisualGenerationPipeline", | |
| "_diffusers_version": "0.21.2", | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPImageProcessor" | |
| ], | |
| "multimodal_encoder": [ | |
| "transformers_modules.multimodal_encoder.modeling_emu", | |
| "EmuForCausalLM" | |
| ], | |
| "safety_checker": [ | |
| "stable_diffusion", | |
| "StableDiffusionSafetyChecker" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "LlamaTokenizerFast" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |