🚨 Day 8/8: OpenMed Medical Reasoning Dataset Release - THE GRAND FINALE 
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🚨 Day 8/8: OpenMed Medical Reasoning Dataset Release - THE GRAND FINALE 
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Today I complete my 8-day release series with Medical-Reasoning-SFT-Mega.
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Today I complete my 8-day release series with Medical-Reasoning-SFT-Mega.
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The largest open medical reasoning dataset, combining 7 state-of-the-art AI models with fair distribution deduplication.
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The largest open medical reasoning dataset, combining 7 state-of-the-art AI models with fair distribution deduplication.
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THE 7 SOURCE MODELS (Original Sample Counts):
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THE 7 SOURCE MODELS (Original Sample Counts):
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1. Trinity-Mini: 810,284 samples
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1. Trinity-Mini: 810,284 samples
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2. Qwen3-Next-80B: 604,249 samples
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2. Qwen3-Next-80B: 604,249 samples
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3. GPT-OSS-120B: 506,150 samples
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3. GPT-OSS-120B: 506,150 samples
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4. Nemotron-Nano-30B: 444,544 samples
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4. Nemotron-Nano-30B: 444,544 samples
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5. GLM-4.5-Air: 225,179 samples
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5. GLM-4.5-Air: 225,179 samples
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6. MiniMax-M2.1: 204,773 samples
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6. MiniMax-M2.1: 204,773 samples
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7. Baichuan-M3-235B: 124,520 samples
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7. Baichuan-M3-235B: 124,520 samples
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TOTAL BEFORE DEDUPLICATION: 2,919,699 samples
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TOTAL BEFORE DEDUPLICATION: 2,919,699 samples
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TOKEN COUNTS:
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TOKEN COUNTS:
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- Content tokens: 2.22 Billion
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- Content tokens: 2.22 Billion
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- Reasoning tokens: 1.56 Billion
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- Reasoning tokens: 1.56 Billion
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- Total tokens: 3.78 Billion
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- Total tokens: 3.78 Billion
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- Samples with chain-of-thought: 100%
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- Samples with chain-of-thought: 100%
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Quick Start:
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Quick Start:
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from datasets import load_dataset
ds = load_dataset("OpenMed/Medical-Reasoning-SFT-Mega")
```
from datasets import load_dataset
ds = load_dataset("OpenMed/Medical-Reasoning-SFT-Mega")
```
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All datasets Apache 2.0 licensed. Free for research and commercial use.
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All datasets Apache 2.0 licensed. Free for research and commercial use.
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Thank you for following OpenMed's release series. I can't wait to see what you build. 🔥
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Thank you for following OpenMed's release series. I can't wait to see what you build. 🔥
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https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Mega
OpenMed/Medical-Reasoning-SFT-Mega
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Mega
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https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
new_line
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Trinity-Mini
OpenMed/Medical-Reasoning-SFT-Trinity-Mini
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Trinity-Mini
new_line
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
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https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
new_line
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
new_line
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
dataset
resource
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
new_line
https://huggingface.co/datasets/OpenMed/Medical-Reasonin
https://huggingface.co/datasets/OpenMed/Medical-Reasonin
link
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https://huggingface.co/collections/OpenMed/medical-datasets
https://huggingface.co/collections/OpenMed/medical-datasets
link
🚨 Day 8/8: OpenMed Medical Reasoning Dataset Release - THE GRAND FINALE 

Today I complete my 8-day release series with Medical-Reasoning-SFT-Mega.
The largest open medical reasoning dataset, combining 7 state-of-the-art AI models with fair distribution deduplication.

THE 7 SOURCE MODELS (Original Sample Counts):

1. Trinity-Mini: 810,284 samples
2. Qwen3-Next-80B: 604,249 samples
3. GPT-OSS-120B: 506,150 samples
4. Nemotron-Nano-30B: 444,544 samples
5. GLM-4.5-Air: 225,179 samples
6. MiniMax-M2.1: 204,773 samples
7. Baichuan-M3-235B: 124,520 samples

TOTAL BEFORE DEDUPLICATION: 2,919,699 samples

TOKEN COUNTS:
- Content tokens: 2.22 Billion
- Reasoning tokens: 1.56 Billion
- Total tokens: 3.78 Billion
- Samples with chain-of-thought: 100%

Quick Start:
```
from datasets import load_dataset
ds = load_dataset("OpenMed/Medical-Reasoning-SFT-Mega")
```

All datasets Apache 2.0 licensed. Free for research and commercial use.

Thank you for following OpenMed's release series. I can't wait to see what you build. 🔥

https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Mega
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Trinity-Mini
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
https://huggingface.co/datasets/OpenMed/Medical-Reasonin

https://huggingface.co/collections/OpenMed/medical-datasets
🔥
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