# Dataset Card for sambanova_deit_data

## Dataset Description


This is output data from the Sambanova SN30. Each file is named based on which model it came from.
The data is in the form of 3-element tuples per sample from the Imagenet-1k validation dataset. Each tuple contains: logits (Python list), sample name (string), Imagenet label (int).
The included python script contains a function that will extract all data into a dictionary, with the model name that they came from as the keys.

size_categories:100K<n<1M license:afl-3.0 code region:us
{"license": "afl-3.0", "size_categories": ["100K<n<1M"], "pretty_name": "Output Results From the Sambanova SN30", "tags": ["code"]}
TAGS
#size_categories-100K<n<1M #license-afl-3.0 #code #region-us 

# Dataset Card for sambanova_deit_data

## Dataset Description


This is output data from the Sambanova SN30. Each file is named based on which model it came from.
The data is in the form of 3-element tuples per sample from the Imagenet-1k validation dataset. Each tuple contains: logits (Python list), sample name (string), Imagenet label (int).
The included python script contains a function that will extract all data into a dictionary, with the model name that they came from as the keys.

# Dataset Card for sambanova_deit_data ## Dataset Description


This is output data from the Sambanova SN30. Each file is named based on which model it came from.
The data is in the form of 3-element tuples per sample from the Imagenet-1k validation dataset. Each tuple contains: logits (Python list), sample name (string), Imagenet label (int).
The included python script contains a function that will extract all data into a dictionary, with the model name that they came from as the keys.
TAGS
#size_categories-100K<n<1M #license-afl-3.0 #code #region-us 
 # Dataset Card for sambanova_deit_data ## Dataset Description


This is output data from the Sambanova SN30. Each file is named based on which model it came from.
The data is in the form of 3-element tuples per sample from the Imagenet-1k validation dataset. Each tuple contains: logits (Python list), sample name (string), Imagenet label (int).
The included python script contains a function that will extract all data into a dictionary, with the model name that they came from as the keys.