afrideva / gpt2-small-danish-GGUF

KennethTM/gpt2-small-danish-GGUF

Quantized GGUF model files for gpt2-small-danish from KennethTM

Original Model Card:

What is this?

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 library:

from transformers import pipeline

generator = pipeline("text-generation", model = "KennethTM/gpt2-small-danish")
text = generator("Manden arbejdede som")

print(text[0]["generated_text"])

Or load it using the Auto* classes:

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 ('unshuffled_deduplicated_da') and a context length of 1024 tokens.

The model weights are initialized from the English GPT-2 small model with new word token embeddings created for Danish using WECHSEL .

Initially, only the word token embeddings are trained using 50.000 samples. Finally, the whole model is trained using 1.000.000 samples.

For reference, the model achieves a perplexity of 33.5 on 5.000 random validation samples.

Model training is carried out on an 8 GB GPU.

Notes

This is a pre-trained model, for optimal performance it should be finetuned for new tasks.