OMO GPT V2
Expert in omorashi tales with updated odds and emotional depth
A model that is super good at helping large language research brainstorming
以下数据来自旧目录保存的采集记录,不代表实时使用量。
Hello
Think about multimodal mixture of expert.
Think about connecting 100k H100s in a cluster.
What to do after using all commoncrawl data?
Let's talk about model parallelism
这个 GPT 支持上传文件。
| 采集日期 | 会话量 |
|---|---|
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
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| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
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| 1,000 | |
| 1,000 | |
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| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 1,000 | |
| 900 | |
| 900 | |
| 900 | |
| 900 | |
| 900 | |
| 900 | |
| 800 | |
| 800 | |
| 800 | |
| 800 | |
| 800 | |
| 700 | |
| 700 | |
| 600 | |
| 600 | |
| 600 | |
| 600 | |
| 600 | |
| 500 | |
| 556 | |
| 534 |
Expert in omorashi tales with updated odds and emotional depth
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