Row 76030
Content Data
This page contains data entry 76030 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
phi models are built for an agentic environment, period.
The scientists behind those models have no reason to train their models on benchmark data, I really don't know why I keep listening this all the time.
phi models are result of training a LM on synthetic, potentially very high data quality (e.g. gpt4 outputs or similar) and that's a very interesting point of research that nobody has yet explored, apart from them.
They are supposed to be finetuned on specific tasks, they are boring, that's also why they suck on the leaderboards.
Moreover, they've lower capacity so tend to perform worse on "in the wild" prompts.
If you'll ever have to train a LLM at scale, trust me, you'll wish there was a smarter and cheaper way.
| Field | Value |
|---|---|
| text | phi models are built for an agentic environment, period. The scientists behind those models have no reason to train their models on benchmark data, I really don't know why I keep listening this all the time. phi models are result of training a LM on synthetic, potentially very high data quality (e.g. gpt4 outputs or similar) and that's a very interesting point of research that nobody has yet explored, apart from them. They are supposed to be finetuned on specific tasks, they are boring, tha… |
| label | r/machinelearning |
| dataType | comment |
| communityName | r/MachineLearning |
| datetime | 2024-05-24 |
| username_encoded | Z0FBQUFBQm5Lak1pUVlmZUdNVVFmdEE4UHNfOWN5dFVQOHdiaHVJQnEtS0pjdE1sX3NWLWJONTlCQ3l1bkNhMjlLVEI1RjRpZXlaQlk2UE9QQV9PWmwxUFBzSnJmbDJYV1E9PQ== |
| url_encoded | Z0FBQUFBQm5Lak96V2JNVkdMNy1oSGptMUdMWGU4dkhBcTlMaGprYThGbTNTVjNGdU91QTlSOUFvVVkyQTZNQ1VwbVJ2aGJpZzlfZGtwODc1ZVZqYThrNmlYazgtcTZvcVZ4Tzl2V1Vhd3FuUzN0d3pXWDlnNXZQU1RJRGMxZ25VOXJFNWhHcG5TNkpBLS1lNEo2OXFRVmRJZDRUQnNVaEVOeG02cWlMazZ4dEZhOTVlTVpESlFrZnltRlFpa3pSdTR1amZqa1RhNEdKVk9BcE1QR2tvMUxpU1VKNkp5dHFYUT09 |
Raw Record
{
"text": "phi models are built for an agentic environment, period. \n\nThe scientists behind those models have no reason to train their models on benchmark data, I really don't know why I keep listening this all the time.\n\nphi models are result of training a LM on synthetic, potentially very high data quality (e.g. gpt4 outputs or similar) and that's a very interesting point of research that nobody has yet explored, apart from them. \n\nThey are supposed to be finetuned on specific tasks, they are boring, that's also why they suck on the leaderboards. \n\nMoreover, they've lower capacity so tend to perform worse on \"in the wild\" prompts.\n\nIf you'll ever have to train a LLM at scale, trust me, you'll wish there was a smarter and cheaper way.",
"label": "r/machinelearning",
"dataType": "comment",
"communityName": "r/MachineLearning",
"datetime": "2024-05-24",
"username_encoded": "Z0FBQUFBQm5Lak1pUVlmZUdNVVFmdEE4UHNfOWN5dFVQOHdiaHVJQnEtS0pjdE1sX3NWLWJONTlCQ3l1bkNhMjlLVEI1RjRpZXlaQlk2UE9QQV9PWmwxUFBzSnJmbDJYV1E9PQ==",
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}
Entry Information
- Entry ID: 76030
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000