# Dataset Card for "tokenized-recipe-nlg-gpt2"

This a tokenized version of the recipe-nlg database from https://recipenlg.cs.put.poznan.pl/. 
The preprocessing on the original csv was done using the methodology of the original paper (best as I could interpret) along with a similar 0.05 percent train test split. The tokenizer used has some special tokens, but all these parameters are accessible in https://huggingface.co/pratultandon/recipe-nlg-gpt2 if you want to recreate. This dataset will save you a lot of time getting started if you want to experiment with training GPT2 on the data yourself. 


region:us
{"dataset_info": {"features": [{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}], "splits": [{"name": "test", "num_bytes": 135944246, "num_examples": 106202}, {"name": "train", "num_bytes": 2582090838, "num_examples": 2022671}], "download_size": 805955428, "dataset_size": 2718035084}}
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#region-us 

# Dataset Card for "tokenized-recipe-nlg-gpt2"

This a tokenized version of the recipe-nlg database from URL 
The preprocessing on the original csv was done using the methodology of the original paper (best as I could interpret) along with a similar 0.05 percent train test split. The tokenizer used has some special tokens, but all these parameters are accessible in URL if you want to recreate. This dataset will save you a lot of time getting started if you want to experiment with training GPT2 on the data yourself. 


# Dataset Card for "tokenized-recipe-nlg-gpt2"

This a tokenized version of the recipe-nlg database from URL 
The preprocessing on the original csv was done using the methodology of the original paper (best as I could interpret) along with a similar 0.05 percent train test split. The tokenizer used has some special tokens, but all these parameters are accessible in URL if you want to recreate. This dataset will save you a lot of time getting started if you want to experiment with training GPT2 on the data yourself.
TAGS
#region-us 
 # Dataset Card for "tokenized-recipe-nlg-gpt2"

This a tokenized version of the recipe-nlg database from URL 
The preprocessing on the original csv was done using the methodology of the original paper (best as I could interpret) along with a similar 0.05 percent train test split. The tokenizer used has some special tokens, but all these parameters are accessible in URL if you want to recreate. This dataset will save you a lot of time getting started if you want to experiment with training GPT2 on the data yourself.