--- language: - en license: apache-2.0 task_categories: - question-answering - text-generation tags: - reinforcement-learning-from-human-feedback - reinforcement-learning - dialogue - conversational-ai - preference-alignment dataset_info: - config_name: feedback_decoder_binary features: - name: predictions dtype: int64 - name: labels dtype: int64 - name: game_turn_id dtype: string - name: text dtype: string splits: - name: train num_bytes: 5115528 num_examples: 7003 download_size: 651037 dataset_size: 5115528 - config_name: feedback_decoder_ternary features: - name: predictions dtype: int64 - name: labels dtype: int64 - name: game_turn_id dtype: string - name: text dtype: string splits: - name: train num_bytes: 4936671 num_examples: 7003 download_size: 640213 dataset_size: 4936671 - config_name: human_eval features: - name: correctness dtype: string - name: feedback dtype: string - name: delta_clicks sequence: string - name: game_id dtype: string - name: turn_id dtype: int64 - name: round dtype: int64 - name: policy_name dtype: string - name: targets sequence: string - name: selected sequence: string - name: deselected sequence: string - name: context sequence: string - name: end dtype: int8 - name: currently_selected sequence: string splits: - name: train num_bytes: 3190406 num_examples: 8111 download_size: 347537 dataset_size: 3190406 - config_name: interaction features: - name: game_id dtype: string - name: turn dtype: int64 - name: end dtype: string - name: s comments dtype: string - name: speaker dtype: string - name: len dtype: string - name: clicks sequence: sequence: string - name: context sequence: string - name: targets sequence: string - name: chat sequence: string - name: dataset_alias dtype: string - name: policy_name dtype: string - name: date dtype: date32 - name: round dtype: int64 splits: - name: train num_bytes: 8775426 num_examples: 7920 download_size: 2120499 dataset_size: 8775426 - config_name: turn features: - name: chats sequence: string - name: clicks sequence: sequence: string - name: targets sequence: string - name: game_id dtype: string - name: end dtype: int8 - name: context sequence: string - name: turn_id dtype: int8 - name: currently_selected sequence: string - name: deselected sequence: string - name: selected sequence: string - name: chat_feedback dtype: string - name: game_turn_id dtype: string - name: prob_action dtype: float64 - name: dataset_alias dtype: string - name: policy_name dtype: string - name: date dtype: date32 - name: round dtype: int64 splits: - name: train num_bytes: 45674609 num_examples: 59431 download_size: 6438021 dataset_size: 45674609 configs: - config_name: feedback_decoder_binary data_files: - split: train path: feedback_decoder_binary/train-* - config_name: feedback_decoder_ternary data_files: - split: train path: feedback_decoder_ternary/train-* - config_name: human_eval data_files: - split: train path: human_eval/train-* - config_name: interaction data_files: - split: train path: interaction/train-* - config_name: turn data_files: - split: train path: turn/train-* --- # Retrospective Learning from Interactions (Respect) Dataset This repository contains the `lil-lab/respect` data, based on the ACL paper [Retrospective Learning from Interactions](https://huggingface.co/papers/2410.13852). For more resources, please see and . ## Sample Usage You can load the data and associated checkpoints as follows: ```python from datasets import load_dataset from transformers import Idefics2ForConditionalGeneration from peft import PeftModel import torch # Ensure torch is imported # Download data ds = load_dataset("lil-lab/respect", name="turn", split="train") # Download checkpoints checkpoint = "HuggingFaceM4/idefics2-8b" model_id = 'lil-lab/respect' model = Idefics2ForConditionalGeneration.from_pretrained( checkpoint, torch_dtype=torch.bfloat16) peft_model = PeftModel.from_pretrained( model, model_id, adapter_name="r6_bp", revision="r6_bp") ```