Row 4855
Content Data
This page contains data entry 4855 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
Heard from two independent sources at MSFT (one close to Sebastien Bubeck) about the upcoming Phi-3 models:
* Three different sized models (up to 14B) * Again, mostly synthetic and LLM-augmented training data * Apparently some upscaling techniques on the training side * No more Apache 2 but more restrictive license (similar to llama3) * Mixtral level performance with much fewer parameters
I wanted to see if anyone has more insider information about the models.
| Field | Value |
|---|---|
| text | Heard from two independent sources at MSFT (one close to Sebastien Bubeck) about the upcoming Phi-3 models: * Three different sized models (up to 14B) * Again, mostly synthetic and LLM-augmented training data * Apparently some upscaling techniques on the training side * No more Apache 2 but more restrictive license (similar to llama3) * Mixtral level performance with much fewer parameters I wanted to see if anyone has more insider information about the models. |
| label | r/machinelearning |
| dataType | post |
| communityName | r/MachineLearning |
| datetime | 2024-04-23 |
| username_encoded | Z0FBQUFBQm5LakwyOFB1WmhtV2JpU3ZCZjBGVXJxNkJJeVFnYVFiWnVrQWFnZ1AwR3hrREUydDdCOHlaS0x1bjZrTDFEcXNVN2JST1pnV0RBbU1meFNiZlV0T1J5UEltLUE9PQ== |
| url_encoded | Z0FBQUFBQm5Lak9GckIzT19teXpPbGsyUFh5eDRUdmhKaUt2V3JPYXdOQkpzTnNQRnppYjN5TWJ5UW9GOEN3UGF4QS16RkNWajl3aEhRdTVVSS1yVEtqTTBZc1EyRy1BWWhEQ2h5dk5xR21NWi1BdGRDMDQ0dW9PaGg0OG1zbmQ0NktIOG1pc2JzLVdnY0drNjdaczJZUkNBalJuWXNsNVJBZ1VaV3N6RGJOb2tJMWlST2dUa2htaVBmUFNSZFNiT1E2UnJjN1poLUFr |
Raw Record
{
"text": "Heard from two independent sources at MSFT (one close to Sebastien Bubeck) about the upcoming Phi-3 models:\n\n* Three different sized models (up to 14B)\n* Again, mostly synthetic and LLM-augmented training data\n* Apparently some upscaling techniques on the training side\n* No more Apache 2 but more restrictive license (similar to llama3)\n* Mixtral level performance with much fewer parameters\n\nI wanted to see if anyone has more insider information about the models.",
"label": "r/machinelearning",
"dataType": "post",
"communityName": "r/MachineLearning",
"datetime": "2024-04-23",
"username_encoded": "Z0FBQUFBQm5LakwyOFB1WmhtV2JpU3ZCZjBGVXJxNkJJeVFnYVFiWnVrQWFnZ1AwR3hrREUydDdCOHlaS0x1bjZrTDFEcXNVN2JST1pnV0RBbU1meFNiZlV0T1J5UEltLUE9PQ==",
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}
Entry Information
- Entry ID: 4855
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000