datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dolphinDolphin 🐬
https://erichartford.com/dolphin
Dataset details
This dataset is an attempt to replicate the results of Microsoft's Orca
Our dataset consists of:
~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m… See the full description on the dataset page: https://huggingface.co/datasets/QuixiAI/dolphin.QuixiAI-dolphin-distill
Clean QuixiAI/dolphin-distill dataset
This is an unofficial, reformatted version of QuixiAI/dolphin-distill.
It contains mostly English instruction following and conversation datasets.
Major changes:
only kept the longest valid conversation from each row (optional system prompt, followed by alternating user and gpt turns)
duplicate rows removed
URLs, e-mail addresses, phone numbers, API keys and tokens redacted
shuffled and split into chunks
This filtered the original 11,625,521… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/QuixiAI-dolphin-distill.dolphin-ru
Dolphin-ru 🐬
This is translated version of ehartford/dolphin into Russian.
dolphin-sft-v0.1-preferenceThe preference dataset was generated using Mistral-Instruct-v0.1 finetuned on a GPT-4 subset of the Dolphin dataset (16k samples). Link to the model.
Generated responses are labeled as rejected, GPT-4 responses (original Dolphin data) are labeled as accepted.
The motivation was to test out the SPIN paper finetuning methodology.
QuixiAI-dolphin_DatasetDolphin 🐬
https://erichartford.com/dolphin
Dataset details
This dataset is an attempt to replicate the results of Microsoft's Orca
Our dataset consists of:
~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m… See the full description on the dataset page: https://huggingface.co/datasets/Maximiliano-Flores-Dev/QuixiAI-dolphin_Dataset.dolphin-r1-korean-deepseek-parsed
[PARSED] dolphin R1 korean deepseek (toolcalls)
The data in this dataset is a subset of the original exp-models/dolphin-r1-korean-deepseek-toolcalls*Dropped row 1273 due to surrogates error.
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
dolphin-r1-korean-deepseek
no
yes
yes
tool_calls
1757
dolphin-r1-korean-deepseek-non-reasoning
no
yes
yes
tool_calls
1757
This dataset is a re-parsed version of… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/dolphin-r1-korean-deepseek-parsed.MaritimeBench
Maritime Bench
本评测集是航运行业首个基于“学科(一级)- 子学科(二级)- 具体考点(三级)”分类体系打造的专业知识评测集,包含1888道客观选择题,覆盖航海、轮机、电子电气员、GMDSS及船员培训等核心领域。评测内容涵盖理论知识、操作技能和行业规范,旨在提升航运领域AI模型的理解与推理能力,确保其在关键知识上的准确性和适应性。同时,本评测集可为航运专业考试、船员培训及资质认证提供自动化测评支持,并优化船舶管理、导航操作、海上通信等场景中的智能问答与决策系统。
MaritimeBench基于行业权威标准,构建了系统、科学的航运知识评测体系,全面评估模型在航海、轮机、电子电气员、GMDSS及船员培训等领域的表现。评测内容深入理论、实践与规范,助力提升AI模型的专业能力。
MaritimeBench评测集亮点
权威性:严格遵循航运行业标准,确保评测科学、实用。
精准分类:采用“学科-子学科-考点”三级框架,评测更具针对性和可扩展性。… See the full description on the dataset page: https://huggingface.co/datasets/Hi-Dolphin/MaritimeBench.dolphin_deA german translation for the cognitivecomputations/dolphin dataset.
Extracted from seedboxventures/multitask_german_examples_32k.
Translation created by seedbox ai for KafkaLM ❤️.
Available for finetuning in hiyouga/LLaMA-Factory.
dolphin-only-gpt-4Dolphin 🐬
https://erichartford.com/dolphin
Dataset details
This dataset is an attempt to replicate the results of Microsoft's Orca
Our dataset consists of:
~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m… See the full description on the dataset page: https://huggingface.co/datasets/polymer/dolphin-only-gpt-4.ru_dolphin-r1_v1dolphinDolphin 🐬
https://erichartford.com/dolphin
Dataset details
This dataset is an attempt to replicate the results of Microsoft's Orca
Our dataset consists of:
~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m… See the full description on the dataset page: https://huggingface.co/datasets/Imunlucky/dolphin.dolphinDolphin 🐬
https://erichartford.com/dolphin
Dataset details
This dataset is an attempt to replicate the results of Microsoft's Orca
Our dataset consists of:
~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m… See the full description on the dataset page: https://huggingface.co/datasets/pperojas/dolphin.dolphin_5k_testTiny Dolphin 🐬
see https://erichartford.com/dolphin
Dataset details
This dataset is an extract of ~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl). It is derived from this dataset
Loading
dataset = load_dataset("tog/dolphin_5k_test)
This dataset is licensed apache-2.0 for commercial or non-commercial use.
dolphin
Dataset Card for "Dolphin"
This Dataset is edited version of cognitivecomputations/dolphin which
only contains conversations and GPT-4 Responses to make it easier to use it with SFTTrinaer
