Create README.md

README.md

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+---
+language: id
+tags:
+  - gpt2-indo-small-kids-stories
+license: mit
+widget:
+  - text: "Archie sedang mengendarai roket ke planet Mars."
+---
+
+## GPT-2 Indonesian Small Kids Stories
+
+GPT-2 Indonesian Small Kids Stories is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. The model was originally the pre-trained [GPT2 Small Indonesian](https://huggingface.co/flax-community/gpt2-small-indonesian) model, which was then fine-tuned on Indonesian kids' stories from [Room To Read](https://literacycloud.org/) and [Let's Read](https://reader.letsreadasia.org/).
+
+10% of the dataset was kept for evaluation purposes. The pre-trained model was fine-tuned and achieved an evaluation loss of 3.777 and an evaluation perplexity of 43.68.
+
+Hugging Face's `Trainer` class from the [Transformers](https://huggingface.co/transformers) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with other frameworks nonetheless.
+
+## Model
+
+| Model                          | #params | Arch.      | Training/Validation data (text)   |
+| ------------------------------ | ------- | ---------- | --------------------------------- |
+| `gpt2-indo-small-kids-stories` | 124M    | GPT2 Small | Indonesian Kids' Stories (860 KB) |
+
+## Evaluation Results
+
+The model was fine-tuned for 10 epochs.
+
+| Epoch | Training Loss | Validation Loss |
+| ----- | ------------- | --------------- |
+| 1     | 4.259600      | 4.020201        |
+| 2     | 3.979100      | 3.911295        |
+| 3     | 3.818300      | 3.849313        |
+| 4     | 3.691600      | 3.809931        |
+| 5     | 3.589300      | 3.789201        |
+| 6     | 3.506200      | 3.778665        |
+| 7     | 3.439200      | 3.774871        |
+| 8     | 3.387600      | 3.774859        |
+| 9     | 3.351300      | 3.776672        |
+| 10    | 3.330100      | 3.776935        |
+
+## How to Use (PyTorch)
+
+### As Causal Language Model
+
+```python
+from transformers import pipeline
+
+pretrained_name = "bookbot/gpt2-indo-small-kids-stories"
+
+nlp = pipeline(
+    "text-generation",
+    model=pretrained_name,
+    tokenizer=pretrained_name
+)
+
+nlp("Archie sedang mengendarai roket ke planet Mars.")
+```
+
+### Feature Extraction in PyTorch
+
+```python
+from transformers import GPT2LMHeadModel, GPT2TokenizerFast
+
+pretrained_name = "bookbot/gpt2-indo-small-kids-stories"
+model = GPT2LMHeadModel.from_pretrained(pretrained_name)
+tokenizer = GPT2TokenizerFast.from_pretrained(pretrained_name)
+
+prompt = "Archie sedang mengendarai roket ke planet Mars."
+encoded_input = tokenizer(prompt, return_tensors='pt')
+output = model(**encoded_input)
+```
+
+## Disclaimer
+
+Do consider the biases which come from both the pre-trained GPT-2 model and the Indonesian Kids' Stories dataset that may be carried over into the results of this model.
+
+## Author
+
+GPT-2 Indonesian Small Kids Stories was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Google Colaboratory using their free GPU access.