clone
Datasets
All datasets matching “clone”CloneDataimagenet.int8
Imagenet.int8: Entire Imagenet dataset in 5GB
original, reconstructed from float16, reconstructed from uint8
Find 138 GB of imagenet dataset too bulky? Did you know entire imagenet actually just fits inside apple watch?
Resized, Center-croped to 256x256
VAE compressed with SDXL's VAE
Further quantized to int8 near-lossless manner, compressing the entire training dataset of 1,281,167 images down to just 5GB!
Introducing Imagenet.int8, the new MNIST of 2024. After the great… See the full description on the dataset page: https://huggingface.co/datasets/cloneofsimo/imagenet.int8.code_x_glue_cc_clone_detection_big_clone_bench
Dataset Card for "code_x_glue_cc_clone_detection_big_clone_bench"
Dataset Summary
CodeXGLUE Clone-detection-BigCloneBench dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-BigCloneBench
Given two codes as the input, the task is to do binary classification (0/1), where 1 stands for semantic equivalence and 0 for others. Models are evaluated by F1 score.
The dataset we use is BigCloneBench and filtered following the paper… See the full description on the dataset page: https://huggingface.co/datasets/google/code_x_glue_cc_clone_detection_big_clone_bench.reazon-speech-v2-clone
Reazon Speech v2 dataset mirror
Original Dataset Source
Hugging Face Dataset Page: reazon-research/reazonspeech
Project Page: Reazon Research
License
This dataset is a mirror of the original Reazon Speech v2 dataset, but on 🤗 server (so may be faster). This dataset is licensed under the CDLA-Sharing-1.0. The original dataset comes with the following restriction:
TO USE THIS DATASET, YOU MUST AGREE THAT YOU WILL USE THE DATASET SOLELY FOR THE PURPOSE OF… See the full description on the dataset page: https://huggingface.co/datasets/litagin/reazon-speech-v2-clone.tts-pretrain-clones-3m-mos
TTS Pretrain Clones (3M) — with DNSMOS
This is SynDataLab/tts-pretrain-clones-3m
with an added per-utterance dnsmos column (DNSMOS P.835 OVRL score, float32),
computed with the sig_bak_ovr.onnx model.
2,967,779 clone utterances across 2971 English speakers.
Sample rate: 44.1 kHz, WAV in Parquet
dnsmos: overall MOS quality estimate per utterance (higher is better)
Generated by echo-tts synthesizing English text on speaker latents
derived from Qwen3-TTS VoiceDesign base speakers.… See the full description on the dataset page: https://huggingface.co/datasets/SynDataLab-EN/tts-pretrain-clones-3m-mos.laion-pop-vae-t5