datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fire-smoke-hardnegatives-int8in1k.int8it's like imagenet.int8 but
train+val in1k (1,331,168 samples)
flux-dev vae, latent (after dequant) channels scaled to N(0,1)
quantization uses int8 not uint8 (scaling factor 127/4)
basic decode test:
# huggingface-cli download --repo-type dataset main-horse/in1k.int8 --revision flux-1.0-dev --local-dir ./imagenet_int8
import torch
from streaming import StreamingDataset
import streaming.base.util as util
from diffusers import AutoencoderKL
from diffusers.image_processor import… See the full description on the dataset page: https://huggingface.co/datasets/main-horse/in1k.int8.