deepseek-v3
jailbreak-deepseek-v3.2-expsynthetic-medical-conversations-deepseek-v3
🍎 Synthetic Multipersona Doctor Patient Conversations.
Author: Nisten Tahiraj
License: MIT
🧠 Generated by DeepSeek V3 running in full BF16.
🛠️ Done in a way that includes induced errors/obfuscations by the AI patients and friendly rebutals and corrected diagnosis from the AI doctors. This makes the dataset very useful as both training data and retrival systems for reducing hallucinations and increasing the diagnosis quality.
🐧 Conversations… See the full description on the dataset page: https://huggingface.co/datasets/OnDeviceMedNotes/synthetic-medical-conversations-deepseek-v3.logiqa-deepseek-v3synthetic-medical-conversations-deepseek-v3-chatTaken from Synthetic Multipersona Doctor Patient Conversations. by Nisten Tahiraj.
Original README
🍎 Synthetic Multipersona Doctor Patient Conversations.
Author: Nisten Tahiraj
License: MIT
🧠 Generated by DeepSeek V3 running in full BF16.
🛠️ Done in a way that includes induced errors/obfuscations by the AI patients and friendly rebutals and corrected diagnosis from the AI doctors. This makes the dataset very useful as both training data and retrival… See the full description on the dataset page: https://huggingface.co/datasets/MaziyarPanahi/synthetic-medical-conversations-deepseek-v3-chat.eval-DeepSeek-V3-0324
dsv3 Evaluation Results
Summary
Benchmark
Score
Metric
Samples
Overlong rate
aime24
0.506
math_pass@1:64_samples
64
100.0%
aime25
0.422
math_pass@1:64_samples
64
100.0%
arenahard
0.926
eval/overall_winrate
500
0.0%
bbh_generative
0.868
extractive_match
1
100.0%
creative-writing-v3
0.767
creative_writing_score
96
0.0%
drop_generative_nous
0.829
drop_acc
1
100.0%
eqbench3
0.831
eqbench_score
135
0.0%
gpqa_diamond
0.680
gpqa_pass@1:8_samples8
100.0%… See the full description on the dataset page: https://huggingface.co/datasets/NousResearch/eval-DeepSeek-V3-0324.DeepSeek-V3-Infinity-Instruct-0625
DeepSeek-V3-Infinity-Instruct-0625
Dataset Description
This dataset is part of the LK-Speculators collection for speculative decoding research. It contains 660K prompt-response pairs designed for training draft models that are used alongside DeepSeek-V3-0324 as the target model. The dataset was created by generating responses to the prompts from Infinity-Instruct-0625 with deepseek-ai/DeepSeek-V3-0324 at temperature=1.
For more details on the training methodology and… See the full description on the dataset page: https://huggingface.co/datasets/nebius/DeepSeek-V3-Infinity-Instruct-0625.