datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Context_window_256
Counter Strike 2 Cheat Detection Context Windows - Length 256
Overview
The Counter Strike 2 Cheat Detection Context Windows - Length 256 (Context_window_256) is a dataset
conprised of "context windows". This dataset was created using extracted data from the
CS2CD dataset. For more
information regarding the data see
AntiCheatPT: A Transformer-Based Approach to Cheat Detection In Competitive Computer Games by Mille Mei Zhen Loo and Gert Lužkov 1/6/2025.… See the full description on the dataset page: https://huggingface.co/datasets/CS2CD/Context_window_256.model-context-windows
LLM Context Windows — 206 models
Context-window sizes for 206 ready models served by the Qubax AI API (OpenAI-compatible), exported from the public /v1/models endpoint.
Columns
Column
Description
model_id
API model identifier
model_name
Display name
context_window_tokens
Max context window (tokens)
max_output_tokens
Max output (tokens, where published)
source
Provenance
Notes
License: CC0 1.0 (public domain) — use freely in… See the full description on the dataset page: https://huggingface.co/datasets/QubaxAI/model-context-windows.Context_window_1024
Counter Strike 2 Cheat Detection Context Windows - Length 1024
Overview
The Counter Strike 2 Cheat Detection Context Windows - Length 1024 (Context_window_1024) is a dataset
conprised of "context windows". This dataset was created using extracted data from the
CS2CD dataset. For more
information regarding the data see
AntiCheatPT: A Transformer-Based Approach to Cheat Detection In Competitive Computer Games by Mille Mei Zhen Loo and Gert Lužkov 1/6/2025.… See the full description on the dataset page: https://huggingface.co/datasets/CS2CD/Context_window_1024.clinical-quad-prior-text-context-window-loss-new-data-summary-extension-hallucination-v0.1What this repo does
This dataset models hallucinated narrative continuation in clinical summaries. It predicts when the interaction between prior text similarity, context window loss, lack of new data, and high summary extension rate indicates that new narrative content has been generated without supporting evidence.
Core quad
prior_text_similarity_index
context_window_loss_index
new_data_presence_index
summary_extension_rate_index
Prediction target
label_hallucinated_continuation
Row… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-prior-text-context-window-loss-new-data-summary-extension-hallucination-v0.1.TRADOC_short_long_context_window_likert_eval_v1