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README.md
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- **Model Type:** Transformer-based language model
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- **Language(s):** English
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- **Base Model:** [GPT2-medium](https://huggingface.co/openai-community/gpt2-medium)
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- **Resources for more information:**
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- [GitHub Repo](https://github.com/valentin-velev29/DLSS-24-GPT-2-Project)
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## How to Get Started with the Model
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```python
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>>> from transformers import pipeline, set_seed
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>>> generator = pipeline('text-generation', model='
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>>> set_seed(42)
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>>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5)
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Here is how to use this model to get the features of a given text in PyTorch:
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output = model(**encoded_input)
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```
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and in TensorFlow:
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```python
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## Uses
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This model is further pretrained to generate artificial product reviews. This can be usefull for:
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## Training
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- **Model Type:** Transformer-based language model
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- **Language(s):** English
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- **Base Model:** [GPT2-medium](https://huggingface.co/openai-community/gpt2-medium)
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- **Resources for more information:** [GitHub Repo](https://github.com/valentin-velev29/DLSS-24-GPT-2-Project)
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## How to Get Started with the Model
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```python
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>>> from transformers import pipeline, set_seed
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>>> generator = pipeline('text-generation', model='TomData/GPT2-review')
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>>> set_seed(42)
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>>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5)
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```
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Here is how to use this model to get the features of a given text in PyTorch:
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output = model(**encoded_input)
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```
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and in TensorFlow:
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```python
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## Uses
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This model is further pretrained to generate artificial product reviews. This can be usefull for:
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- Market research
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- Product analysis
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- Customer preferences
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- Fashion trends
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- Research
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## Training
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