data-chat
GGUF_dataset_avaliev_chat_doctor_unsolth_llama3.1_1b3bconverstionalDATA-AI_Chat_4_Thinking_0.5B-GGUFDATA-AI_Chat_4_0.6B-GGUFKaKee_-_llama-2-7b-chat_own_build_dataset_8th_full_unknown_various_answer_7_epoch1-ggufDATA-AI_Chat_4.1_0.5B-GGUFDATA-AI_Chat_3_360M-11M-Intruct-GGUFDATA-AI_Chat_3_1B-GGUFLlama-2-7b-chat-hf-1k-Databricks-ENG-GGUF
ChatQA-Training-Data
Data Description
We release the training dataset of ChatQA. It is built and derived from existing datasets: DROP, NarrativeQA, NewsQA, Quoref, ROPES, SQuAD1.1, SQuAD2.0, TAT-QA, a SFT dataset, as well as a our synthetic conversational QA dataset by GPT-3.5-turbo-0613. The SFT dataset is built and derived from: Soda, ELI5, FLAN, the FLAN collection, Self-Instruct, Unnatural Instructions, OpenAssistant, and Dolly. For more information about ChatQA, check the website!
Other… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/ChatQA-Training-Data.InternVL-Chat-V1-2-SFT-Data
Data Card for InternVL-Chat-V1-2-SFT-Data
Overview
Inspired by LLaVA-NeXT, we adopted a data-efficient SFT strategy to train InternVL-Chat-V1-2, utilizing approximately 1.2M of visual instruction tuning samples in total, all of which are fully open-source. In a macro sense, we build upon ShareGPT-4V and additionally integrate LLaVA-ZH, DVQA, ChartQA, AI2D, DocVQA, GeoQA+, and SynthDoG-EN. Most of the data remains consistent with LLaVA-NeXT.
Citation
If you use… See the full description on the dataset page: https://huggingface.co/datasets/OpenGVLab/InternVL-Chat-V1-2-SFT-Data.PeptiVerse_datachat_datallm-jp-4-thinking-sft-data-chatmlllm-jpのデータセットllm-jp-4-thinking-sft-dataを、
ChatML形式に変換したものです。
ライセンス
各サンプルのライセンスは、元データセットカードに記載された各データソースのライセンスに従います。
本リポジトリは、元となったデータ全体に対して新たなライセンスを付与するものではありません。
利用する場合は、対応する元データソースのライセンス条件を確認してください。
ChatQA2-Long-SFT-data
Data Description
Here, we release the full long SFT training dataset of ChatQA2. It consists of two parts: long_sft and NarrativeQA_131072. The long_sft dataset is built and derived from existing datasets: LongAlpaca12k, GPT-4 samples from Open Orca, and Long Data Collections. The NarrativeQA_131072 dataset is synthetically generated from NarrativeQA by adding related paragraphs to the given ground truth summary. For the first two steps training of ChatQA-2, we follow ChatQA1.5.
For… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/ChatQA2-Long-SFT-data.