Instructions to use taohu/fastgen-offline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use taohu/fastgen-offline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("taohu/fastgen-offline", 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
| # SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
| # SPDX-License-Identifier: Apache-2.0 | |
| from fastgen.methods.model import FastGenModel as FastGenModel | |
| from fastgen.methods.distribution_matching.dmd2 import DMD2Model as DMD2Model | |
| from fastgen.methods.distribution_matching.ladd import LADDModel as LADDModel | |
| from fastgen.methods.distribution_matching.f_distill import FdistillModel as FdistillModel | |
| from fastgen.methods.distribution_matching.causvid import CausVidModel as CausVidModel | |
| from fastgen.methods.distribution_matching.self_forcing import SelfForcingModel as SelfForcingModel | |
| from fastgen.methods.consistency_model.CM import CMModel as CMModel | |
| from fastgen.methods.consistency_model.TCM import TCMModel as TCMModel | |
| from fastgen.methods.consistency_model.sCM import SCMModel as SCMModel | |
| from fastgen.methods.consistency_model.mean_flow import MeanFlowModel as MeanFlowModel | |
| from fastgen.methods.fine_tuning.sft import SFTModel as SFTModel | |
| from fastgen.methods.fine_tuning.sft import CausalSFTModel as CausalSFTModel | |
| from fastgen.methods.knowledge_distillation.KD import KDModel as KDModel | |
| from fastgen.methods.knowledge_distillation.KD import CausalKDModel as CausalKDModel | |