Any-to-Any
Diffusers
Safetensors
LuminaDiMOOPipeline
llada
Diffusion Large Language Model
Multi-Modal Generation and Understanding
custom_code
Instructions to use Alpha-VLLM/Lumina-DiMOO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alpha-VLLM/Lumina-DiMOO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Alpha-VLLM/Lumina-DiMOO", 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
Add `library_name: transformers` to metadata
#3
by nielsr HF Staff - opened
This PR updates the model card by adding library_name: transformers to the metadata.
Evidence for transformers compatibility:
- The
config.jsonfile contains"transformers_version": "4.46.2"andarchitectures: ["LLaDAForMultiModalGeneration"], along withauto_mapentries that point toconfiguration_llada.LLaDAConfigandmodeling_llada.LLaDAModelLM. - The presence of standard Hugging Face files like
tokenizer.json,special_tokens_map.json,tokenizer_config.json, andgeneration_config.jsonfurther confirms compatibility.
This addition will enable the automated "How to use" widget on the model page, showcasing a code snippet for using the model with the π€ Transformers library, thereby improving its discoverability and ease of use.