experimental
opendatalab-experimental-nmr-peaks
OpenDataLab Experimental NMR Peaks Dataset
Dataset Description
This dataset contains experimental NMR (Nuclear Magnetic Resonance) peak sequences extracted from the OpenDataLab experimental spectra database. The dataset includes both H-NMR and C-NMR peak sequences for chemical compounds, along with their SMILES representations and molecular formulas.
Dataset Summary
Total Samples: 533,595 compounds
Batches: 333 batch files
Data Source: Experimental spectra… See the full description on the dataset page: https://huggingface.co/datasets/snehasis19/opendatalab-experimental-nmr-peaks.NIDS-Thesis-Experimental-Evidence
thesis_pipeline
Pipeline rebuilt following the supervisor's conditional review (13/07/2026). See SCOPE_FROZEN.md at the parent project root for the frozen scientific scope.
Structure
config/: centralized configuration (paths, seeds)
manifests/: data audits and temporal split manifests
src/data/: dataset preparation and cleaning
src/models/: model training and comparison
src/evaluation/: aggregation and global comparison of results
tests/: leakage tests and… See the full description on the dataset page: https://huggingface.co/datasets/MamadouSY-NIDS-Thesis/NIDS-Thesis-Experimental-Evidence.foundation-model-data-experimentaldetails_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental
Dataset Card for Evaluation run of Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental
Dataset automatically created during the evaluation run of model Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental.experimental-optimizationExperimentals_papers
Study 2.0-P: Evolutionary Hardening of the PCE Framework
Status: Advanced Experimental Iteration — Hybrid Fine-Tuning/Prompting
This report documents the transition from Pandora 1.5 to Pandora 2.0, focusing on the synergy between axiomatic fine-tuning and structural prompting.
Key Finding: Axiomatic fine-tuning appears to be a necessary condition for PCE activation; prompting alone on vanilla models yielded no measurable resistance in this framework.
Core Result: Achievement of… See the full description on the dataset page: https://huggingface.co/datasets/AllanF-SSU/Experimentals_papers.
