Instructions to use OzzyGT/idol_custom_blocks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/idol_custom_blocks with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OzzyGT/idol_custom_blocks", 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
File size: 2,245 Bytes
afe9f02 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | # Copyright 2026 Sperid Labs and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from diffusers.configuration_utils import FrozenDict
from diffusers.modular_pipelines.modular_pipeline_utils import ComponentSpec
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
from .gaussian_decoder_idol import IdolGaussianDecoderModel
from .octree_decoder_idol import IdolOctreeDecoderModel
from .transformer_idol import IdolTransformerModel
# The converted weights. The model classes come from this repo, so the weights repo holds no code and loads without
# `trust_remote_code`. Load from elsewhere with
# `pipe.load_components(pretrained_model_name_or_path={"transformer": ..., "octree_decoder": ..., ...})`.
IDOL_WEIGHTS_REPO = "OzzyGT/idol_diffusers"
def transformer_spec() -> ComponentSpec:
return ComponentSpec(
"transformer", IdolTransformerModel, pretrained_model_name_or_path=IDOL_WEIGHTS_REPO, subfolder="transformer"
)
def octree_decoder_spec() -> ComponentSpec:
return ComponentSpec(
"octree_decoder",
IdolOctreeDecoderModel,
pretrained_model_name_or_path=IDOL_WEIGHTS_REPO,
subfolder="octree_decoder",
)
def gaussian_decoder_spec() -> ComponentSpec:
return ComponentSpec(
"gaussian_decoder",
IdolGaussianDecoderModel,
pretrained_model_name_or_path=IDOL_WEIGHTS_REPO,
subfolder="gaussian_decoder",
)
def scheduler_spec() -> ComponentSpec:
# shift 3.0 is the reference's time shift (`rescale_t`)
return ComponentSpec(
"scheduler",
FlowMatchEulerDiscreteScheduler,
config=FrozenDict({"shift": 3.0}),
default_creation_method="from_config",
)
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