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RichardErkhov/
TomData_-_GPT2-review-gguf

Name: TomData_-_GPT2-review-gguf
Availability: InStock

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GPT2-review - GGUF

Model creator: https://huggingface.co/TomData/
Original model: https://huggingface.co/TomData/GPT2-review/

Name	Quant method	Size
GPT2-review.Q2_K.gguf	Q2_K	0.17GB
GPT2-review.Q3_K_S.gguf	Q3_K_S	0.19GB
GPT2-review.Q3_K.gguf	Q3_K	0.21GB
GPT2-review.Q3_K_M.gguf	Q3_K_M	0.21GB
GPT2-review.Q3_K_L.gguf	Q3_K_L	0.23GB
GPT2-review.IQ4_XS.gguf	IQ4_XS	0.22GB
GPT2-review.Q4_0.gguf	Q4_0	0.23GB
GPT2-review.IQ4_NL.gguf	IQ4_NL	0.23GB
GPT2-review.Q4_K_S.gguf	Q4_K_S	0.23GB
GPT2-review.Q4_K.gguf	Q4_K	0.25GB
GPT2-review.Q4_K_M.gguf	Q4_K_M	0.25GB
GPT2-review.Q4_1.gguf	Q4_1	0.25GB
GPT2-review.Q5_0.gguf	Q5_0	0.27GB
GPT2-review.Q5_K_S.gguf	Q5_K_S	0.27GB
GPT2-review.Q5_K.gguf	Q5_K	0.29GB
GPT2-review.Q5_K_M.gguf	Q5_K_M	0.29GB
GPT2-review.Q5_1.gguf	Q5_1	0.29GB
GPT2-review.Q6_K.gguf	Q6_K	0.32GB
GPT2-review.Q8_0.gguf	Q8_0	0.41GB

Original model description:

datasets:

McAuley-Lab/Amazon-Reviews-2023 language:
en library_name: pytorch pipeline_tag: text-generation base_model: openai-community/gpt2-medium

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)

RichardErkhov/TomData_-_GPT2-review-gguf

Original model description:

GPT-2 Medium - Review

Model Details

How to Get Started with the Model

Uses

Training

RichardErkhov/
TomData_-_GPT2-review-gguf