Instructions to use DeltaTechStudios/CourtOfTheAbsurd-host-evidence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeltaTechStudios/CourtOfTheAbsurd-host-evidence with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DeltaTechStudios/CourtOfTheAbsurd-host-evidence", 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
| license: apache-2.0 | |
| tags: | |
| - flux2 | |
| - diffusers | |
| - torchao | |
| - fp8 | |
| - unity | |
| # Court of the Absurd — optional evidence model pack | |
| This repository distributes the optional `host-evidence` 2.1.0 pack used by | |
| Court of the Absurd. It is not a standalone image application. The game | |
| downloads the ZIP, verifies its immutable archive SHA-256, safely extracts it, | |
| then verifies the complete signed per-file manifest before activation. | |
| ## Release artifact | |
| - File: `CourtOfTheAbsurd-host-evidence-2.1.0.zip` | |
| - Installed size: 17,082,671,641 bytes (15.909 GiB) | |
| - Download size: 12,831,802,002 bytes (11.951 GiB) | |
| - SHA-256: `48CE27377D1C482B980291C51778249EB2DC6E569695AB77CB65C748DFC10A5B` | |
| - Manifest: `host-evidence/pack.manifest.json` | |
| The pack contains the Apache-2.0 FLUX.2 Klein 4B components pinned from | |
| `black-forest-labs/FLUX.2-klein-4B`, Photoroom's pinned Diffusers/TorchAO | |
| static-FP8 conversion, and an isolated pinned Windows Python/PyTorch runtime. | |
| Exact upstream revisions are recorded in the game's | |
| `Tools/LocalAI/sources.lock.json`. | |
| ## Runtime profile | |
| The model accepts one to four reference images and is run at four inference | |
| steps. The full-GPU profile is intended for 24 GB RTX 3090/4090-class hosts. | |
| The lower-memory profile keeps the compact static-FP8 transformer resident on | |
| the GPU and offloads text-encoder/VAE weights; its measured PyTorch allocation | |
| peak was 7.94 GiB on the production smoke test. | |
| FLUX.2 Klein 4B and its supplied license are Apache-2.0. TorchAO is | |
| BSD-3-Clause. Upstream attribution and license files are retained in the pack. | |