Instructions to use chenzeyang1/T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chenzeyang1/T with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chenzeyang1/T", torch_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: 760 Bytes
ec755f8 | 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 | """
Default paths for TherA inference (relative to this repository root).
Download model weights into the `weights/` directory — see README.md.
"""
from __future__ import annotations
import sys
from pathlib import Path
PROJECT_ROOT = Path(__file__).resolve().parent
WEIGHTS_DIR = PROJECT_ROOT / "weights"
DEFAULT_CHECKPOINT = WEIGHTS_DIR / "checkpoint"
DEFAULT_MERGED_MODEL = WEIGHTS_DIR / "merged_models"
DEFAULT_PRETRAINED_SD = WEIGHTS_DIR / "stable-diffusion"
DEFAULT_REFERENCE_CACHES = WEIGHTS_DIR / "reference_caches"
def setup_project_path() -> Path:
"""Ensure TherA root is on sys.path so local packages import correctly."""
root = str(PROJECT_ROOT)
if root not in sys.path:
sys.path.insert(0, root)
return PROJECT_ROOT
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