bip
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-long_bipedal_gullSeed-OSS-36B-Instruct-biprojected-norm-preserving-abliterated-i1-GGUFgemma-3-12b-it-norm-preserved-biprojected-abliterated-i1-GGUFBiPS-i1-GGUFBiPS-Chart-i1-GGUFgemma-3-12b-it-biprojected-abliterated-i1-GGUFgemma-3-12b-it-norm-preserved-biprojected-abliterated-GGUFBiPS-Qwen3-i1-GGUF
Datasets
All datasets matching “bip”BiPlayBiPlay contains 9.7 hours of bimanual data collected with an aloha robot at the RAIL lab @ UC Berkeley, USA. It contains 7023 clips, 2000 language annotations and 326 unique scenes.
Paper: https://huggingface.co/papers/2410.10088
Code: https://github.com/sudeepdasari/dit-policy
If you use the dataset please cite:
@inproceedings{dasari2025ingredients,
title={The Ingredients for Robotic Diffusion Transformers},
author={Sudeep Dasari and Oier Mees and Sebastian Zhao and Mohan Kumar Srirama… See the full description on the dataset page: https://huggingface.co/datasets/oier-mees/BiPlay.EEG_records_raw_schizophrenia_bipolarpgc-bipolar
PGC Bipolar Disorder — GWAS Summary Statistics
Dataset Description
Genome-wide association study (GWAS) summary statistics for Bipolar Disorder phenotypes from the Psychiatric Genomics Consortium (PGC).
Each publication is available as a separate subset (config) and can be loaded independently.
Usage
from datasets import load_dataset
# Load a specific GWAS
ds = load_dataset("OpenMed/pgc-bipolar", "bip2011")
print(ds)
List all available subsets… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz041/pgc-bipolar.pgc-bipolar
PGC Bipolar Disorder — GWAS Summary Statistics
Dataset Description
Genome-wide association study (GWAS) summary statistics for Bipolar Disorder phenotypes from the Psychiatric Genomics Consortium (PGC).
Each publication is available as a separate subset (config) and can be loaded independently.
Usage
from datasets import load_dataset
# Load a specific GWAS
ds = load_dataset("OpenMed/pgc-bipolar", "bip2011")
print(ds)
List all… See the full description on the dataset page: https://huggingface.co/datasets/tunahanf/pgc-bipolar.Indirect-Prompt-Injection-BIPIA-GPT
Indirect Prompt Injection Detection Dataset (BIPIA + GPT-4o-mini)
Dataset Summary
This dataset contains 70,000 examples for detecting indirect prompt injection attacks in Large Language Models. It combines:
35,000 malicious samples from the BIPIA benchmark (cleaned and processed)
35,000 benign samples generated using GPT-4o-mini
Indirect prompt injection attacks embed malicious instructions within external content (code, table, email, webAQ, abstract) that LLMs process… See the full description on the dataset page: https://huggingface.co/datasets/MAlmasabi/Indirect-Prompt-Injection-BIPIA-GPT.bipia
geodesic-research/bipia
Auto-generated by dataset-builder.
Each config below is a separate dataset produced from a versioned YAML build
config. Load with:
from datasets import load_dataset
ds = load_dataset("geodesic-research/bipia", "<config_name>", revision="<commit-sha>")
Pin revision= to the specific commit SHA you want; without it, you get the
current HEAD of the dataset repo, which may change when the builder re-pushes.
Configs
Config
Source… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/bipia.