Row 8774

Row ID: 8774 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 8774 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Hi everyone,

I'm planning to fine-tune the LLaVA model and am curious if anyone here has experience with this. Specifically, I'm looking to understand:

1. The size of your dataset (number of images and annotations). 2. How long the fine-tuning process took. 3. Your hardware setup (GPUs, CPUs, RAM). 4. Any specific configuration settings you used.

Thanks in advance

FieldValue
text Hi everyone, I'm planning to fine-tune the LLaVA model and am curious if anyone here has experience with this. Specifically, I'm looking to understand: 1. The size of your dataset (number of images and annotations). 2. How long the fine-tuning process took. 3. Your hardware setup (GPUs, CPUs, RAM). 4. Any specific configuration settings you used. Thanks in advance
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-19
username_encoded Z0FBQUFBQm5Lakw0aVVYUmJweFdHUnNJSzBmbWtucUNRODZNLXFXMDBXVzZNVjh0VzRWRjFYekQ2dWRabEpkZTNDUG5QdkwtaXRkQ3VwOElGXzBVd2pLNjE3MlpyUlE5amc9PQ==
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Raw Record

{
  "text": "Hi everyone,\n\nI'm planning to fine-tune the LLaVA model and am curious if anyone here has experience with this. Specifically, I'm looking to understand:\n\n1. The size of your dataset (number of images and annotations).\n2. How long the fine-tuning process took.\n3. Your hardware setup (GPUs, CPUs, RAM).\n4. Any specific configuration settings you used.\n\nThanks in advance\n\n",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-19",
  "username_encoded": "Z0FBQUFBQm5Lakw0aVVYUmJweFdHUnNJSzBmbWtucUNRODZNLXFXMDBXVzZNVjh0VzRWRjFYekQ2dWRabEpkZTNDUG5QdkwtaXRkQ3VwOElGXzBVd2pLNjE3MlpyUlE5amc9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9IOWQ1Q19GTzN0cG8yRFFpVWlhdnZkcGJDMlJiNm1GYmNfS1RBNThkOXNieDN5SDhLd0I5dURZTDJlV3RsMVFoYlg5WEwtZDE0Zk9sVjA0RXVycXh3S3Z0aXA3SjVlZFRyeFRldGtOSm1UckxLVEU4TF8tMkxwNDRGZVAyZmkybURaVGZCYUhCTTlNU01hV1FxaU1mY1hqdFZRNHNUS3V0S2VoMU9fQnh0eGJUVnZFQXF1bmthcFRRVkZ3TjQ4RnlHQU9VeEd4VEJTdGE5cGFjMFdzNV84QT09"
}
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