Row 80326

Row ID: 80326 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 80326 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

In short, doesn’t matter how fast your GPU is if you can’t fit the model on it (for example, say the next gen 5000 series from Nvidia have a boost in performance so much so an RTX 5060 is 300$ and twice faster than RTX 3090 (which you can get used for like 700$)

if it still has 8/12 GB VRAM you can’t fit the models on it so basically it’s like a supercar that has a really small gas tank so it can go really fast to… nowhere

for DL you have to see how much VRAM you’ll need (based on your needs/models used) and then make a decision from there). For big models it is often better to get dual 3090’s (sometimes only choice if you don’t have money to buy dual 4090’s) because that will give you 48 GB VRAM whereas an RTX 4080 has only 16 GB VRAM

FieldValue
text In short, doesn’t matter how fast your GPU is if you can’t fit the model on it (for example, say the next gen 5000 series from Nvidia have a boost in performance so much so an RTX 5060 is 300$ and twice faster than RTX 3090 (which you can get used for like 700$) if it still has 8/12 GB VRAM you can’t fit the models on it so basically it’s like a supercar that has a really small gas tank so it can go really fast to… nowhere for DL you have to see how much VRAM you’ll need (based on your needs/…
label r/deeplearning
dataType comment
communityName r/deeplearning
datetime 2024-05-24
username_encoded Z0FBQUFBQm5Lak1sNGdrMWdPc25iOHA1YU1UZ3FtZk9jMlQ2SllReWtUd19vUWF4NzA4NEFLM1hwell6N2MwNE1GM09fMTlrUnpmTVVIV3lMcjh3RERYRzBPaXoxS0s0ZzRkWG50cXlHcDRjN3dUMzU4bHNtSmM9
url_encoded Z0FBQUFBQm5Lak8ycDlRZlFvMzJCUkNlX2x4UEYtczVsa2o3SjNCWkFrekdCUmswSFcwWkI0U0ZrWjk1ZlVmMFE1am8xa3NQVEplRGlMNl9aazJEX0RDd2VXZFF5NmZjN2RqTkV0REVaVWpqZUc1MnZkQjU1ZEpSenBGWDlveFZDcjF3dTM2dUtaZFd3cUZ1Y0F1WUx4UUJha0syV0RpYnVjaTNlTHhoTVd1VW11SVlmYTctNV9tLVMtLWFpV2V3cmhUUl9LWHJBS3E0YnNBdzlrSTkxb0tIRjdxREJtZmZmZz09

Raw Record

{
  "text": "In short, doesn’t matter how fast your GPU is if you can’t fit the model on it (for example, say the next gen 5000 series from Nvidia have a boost in performance so much so an RTX 5060 is 300$ and twice faster than RTX 3090 (which you can get used for like 700$) \n\nif it still has 8/12 GB VRAM you can’t fit the models on it so basically it’s like a supercar that has a really small gas tank so it can go really fast to… nowhere\n\nfor DL you have to see how much VRAM you’ll need (based on your needs/models used) and then make a decision from there). For big models it is often better to get dual 3090’s (sometimes only choice if you don’t have money to buy dual 4090’s) because that will give you 48 GB VRAM whereas an RTX 4080 has only 16 GB VRAM",
  "label": "r/deeplearning",
  "dataType": "comment",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-24",
  "username_encoded": "Z0FBQUFBQm5Lak1sNGdrMWdPc25iOHA1YU1UZ3FtZk9jMlQ2SllReWtUd19vUWF4NzA4NEFLM1hwell6N2MwNE1GM09fMTlrUnpmTVVIV3lMcjh3RERYRzBPaXoxS0s0ZzRkWG50cXlHcDRjN3dUMzU4bHNtSmM9",
  "url_encoded": "Z0FBQUFBQm5Lak8ycDlRZlFvMzJCUkNlX2x4UEYtczVsa2o3SjNCWkFrekdCUmswSFcwWkI0U0ZrWjk1ZlVmMFE1am8xa3NQVEplRGlMNl9aazJEX0RDd2VXZFF5NmZjN2RqTkV0REVaVWpqZUc1MnZkQjU1ZEpSenBGWDlveFZDcjF3dTM2dUtaZFd3cUZ1Y0F1WUx4UUJha0syV0RpYnVjaTNlTHhoTVd1VW11SVlmYTctNV9tLVMtLWFpV2V3cmhUUl9LWHJBS3E0YnNBdzlrSTkxb0tIRjdxREJtZmZmZz09"
}
Explore Dataset Explore Row

Entry Information