Updated model card

README.md

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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))
+    ```