Update README.md

README.md

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 # What is this?
 
-GPT-2 model (small version, 124 M parameters) for Danish text generation. 
+A GPT-2 model (small version, 124 M parameters) for Danish text generation. The model was not pre-trained from scratch but adapted from the English version.
+
+# How to use
+
+Test the model using the pipeline from the [🤗 Transformers](https://github.com/huggingface/transformers) library:
+
+```python
+from transformers import pipeline
+
+generator = pipeline("text-generation", model="gpt2-small-danish")
+text = generator("Manden arbejdede som")
+
+print(text[0]["generated_text"])
+```
+
+Or load it using the Auto* classes:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("KennethTM/gpt2-small-danish")
+model = AutoModelForCausalLM.from_pretrained("KennethTM/gpt2-small-danish")
+```
 
 # Model training
 
 The model is trained using the Danish part of the [oscar dataset](https://huggingface.co/datasets/oscar) ('unshuffled_deduplicated_da') and a context length of 1024 tokens.
 
-The model is initilized from the English [GPT-2 small model](https://huggingface.co/gpt2) with new word token embeddings created for Danish using [WECHSEL](https://github.com/CPJKU/wechsel).
+The model is initialized from the English [GPT-2 small model](https://huggingface.co/gpt2) with new word token embeddings created for Danish using [WECHSEL](https://github.com/CPJKU/wechsel).
 
 Initially, only the word token embeddings are trained using 50.000 samples. Finally, the whole model is trained using 1.000.000 samples.
 
-Model training is carried out on a 8 GB GPU.
+Model training is carried out on an 8 GB GPU.
 
 # Notes