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TomData/
GPT2-review

Name: GPT2-review
Rating: 2.5 (11 reviews)

McAuley-Lab/Amazon-Reviews-2023

openai-community/gpt2-medium

finetune

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GPT-2 Medium - Review

Model Details

Model Description: This model is a checkpoint of GPT-2 Medium the 355M parameter version of GPT-2, a transformer-based language model created and released by OpenAI. The model is a further pretrained model on a causal language modeling (CLM) objective with English Amazon Product Reviews from the Fashion category.

Developed by: Students at University of Konstanz
Model Type: Transformer-based language model
Language(s): English
Base Model: GPT2-medium
Resources for more information: GitHub Repo

How to Get Started with the Model

Use the code below to get started with the model. You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we set a seed for reproducibility:

python

>>> from transformers import pipeline, set_seed
>>> generator = pipeline('text-generation', model='TomData/GPT2-review')
>>> set_seed(42)
>>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5)

Here is how to use this model to get the features of a given text in PyTorch:

python

tokenizer = AutoTokenizer.from_pretrained("TomData/GPT2-review")
model = AutoModelForCausalLM.from_pretrained("TomData/GPT2-review")
text = "Replace me by any text you'd like."
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)

and in TensorFlow:

python

tokenizer = AutoTokenizer.from_pretrained("TomData/GPT2-review")
model = AutoModelForCausalLM.from_pretrained("TomData/GPT2-review")
text = "Replace me by any text you'd like."
encoded_input = tokenizer(text, return_tensors='tf')
output = model(encoded_input)

Uses

This model is further pretrained to generate artificial product reviews. This can be usefull for:

Market research
Product analysis
Customer preferences
Fashion trends
Research

Training

The model is further pretrained on the Amazion Review Dataset from McAuley-Lab. For training only the reviews related to the Amazon Fashion category are used. See:

dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_review_Amazon_Fashion", trust_remote_code=True)