datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rejection-sampling-QA
Rejecction Sampling Q&A
This dataset is a very small curated question-answer pairs.
The questions were hand-crafted to test the model's capabilities to follow instruction across various domains.
The answers were generated using Microsoft's Phi-2 and curated using OpenAssistant's Large DeBERTa v3 Reward Model v2.
Dataset Details
The answers of this dataset were generated by prompting Microsoft's Phi-2 using a prompt format inspired by Stanford's Alpaca to help the LLM… See the full description on the dataset page: https://huggingface.co/datasets/alehc/rejection-sampling-QA.demo_rejection_sampling_QA_phi-2_deberta-v3-large-v2_temp0.2This is a demo constructed dataset for alignment/preference learning.
With paritially handcrafted questions (prompts), the answers are genreated by the phi-2 model with temperature 0.2 and the answers are scores select by the deberta-large-v2.
The dataset containing questions and the selected answers from highest to lowest, decoding with rejection sampling K=8.
Example loading:
import datasets
ds = datasets.load_dataset('yizhilll/demo_rejection_sampling_QA_phi-2_deberta-v3-large-v2_temp0.2')… See the full description on the dataset page: https://huggingface.co/datasets/yizhilll/demo_rejection_sampling_QA_phi-2_deberta-v3-large-v2_temp0.2.rejection_sampling_phi_2_OA_rm
Dataset Card for Rejection Sampling Phi-2 with OpenAssistant RM
Dataset Summary
The "Rejection Sampling Phi-2 with OpenAssistant RM" dataset consists of 10 pairs of prompts and responses, which were generated using rejection sampling over 10 Phi-2 generation using the OpenAssistant Reward Model.
Supported Tasks and Leaderboards
The dataset and its creation rationale could be used to support models for question-answering, text-generation, or conversational… See the full description on the dataset page: https://huggingface.co/datasets/alizeepace/rejection_sampling_phi_2_OA_rm.