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---
tags:
- language-model
- transformer-decoder
- tiny-shakespeare
license: mit
datasets:
- tiny_shakespeare
model_description: |
This is a small autoregressive language model based on the Transformer architecture trained on the Tiny Shakespeare dataset.
## Model Description
The model is a custom implementation of a TransformerDecoderModel, which uses a decoder-only architecture similar to GPT-2.
It was trained on the Tiny Shakespeare dataset to generate text in the style of William Shakespeare.
## Training Details
The model was trained and tracked using [Weights & Biases](https://wandb.ai/honcharova-de-hannover/LanguageModel_Project?nw=nwuserhoncharovade).
## How to Use
To generate text with this model, you can load it and the tokenizer as follows:
```python
from transformers import AutoTokenizer
from transformers import GPT2LMHeadModel
# Load the model and tokenizer
model = GPT2LMHeadModel.from_pretrained('NataliaH/TransformerDecoderModel')
tokenizer = AutoTokenizer.from_pretrained('NataliaH/TransformerDecoderModel')
# Provide input text and generate output
input_text = 'To be or not to be'
inputs = tokenizer(input_text, return_tensors='pt')
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
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