45 lines
1.8 KiB
Markdown
45 lines
1.8 KiB
Markdown
---
|
|
license: mit
|
|
language:
|
|
- tr
|
|
pipeline_tag: text-generation
|
|
tags:
|
|
- transformer
|
|
- gpt2
|
|
- turkish
|
|
- baseline
|
|
links:
|
|
- label: "Experiment Paper"
|
|
url: "https://huggingface.co/oguzatas/mamba-tr-project-transformer/resolve/main/OguzhanAtasHW%20state-space-models%20on%20Morphologically%20Rich%20Languages.pdf"
|
|
---
|
|
---
|
|
|
|
[](https://huggingface.co/oguzatas/mamba-tr-project-transformer/resolve/main/OguzhanAtasHW%20state-space-models%20on%20Morphologically%20Rich%20Languages.pdf)
|
|
[](https://colab.research.google.com/drive/1UbkR-i3P6X2cFVWXlntySjki_WBdg0ac?usp=sharing)
|
|
# Transformer Baseline (GPT-2 Style) - Turkish
|
|
|
|
This model serves as the **baseline** for a comparative study between Transformer and Mamba architectures on agglutinative languages (specifically Turkish). It is a decoder-only Transformer model (~111M parameters) trained on the Turkish Wikipedia dataset.
|
|
|
|
## Model Description
|
|
- **Architecture:** GPT-2 (Small)
|
|
- **Parameters:** ~111 Million
|
|
- **Context Length:** 1024
|
|
- **Training Data:** Turkish Wikipedia (Nov 2023)
|
|
- **Purpose:** To provide a performance benchmark for the Mamba architecture.
|
|
|
|
## Usage
|
|
|
|
```python
|
|
from transformers import GPT2LMHeadModel, PreTrainedTokenizerFast
|
|
|
|
model_id = "oguzatas/mamba-tr-project-transformer"
|
|
tokenizer_id = "oguzatas/mamba-tr-project-tokenizer"
|
|
|
|
tokenizer = PreTrainedTokenizerFast.from_pretrained(tokenizer_id)
|
|
model = GPT2LMHeadModel.from_pretrained(model_id)
|
|
|
|
text = "Türkiye'nin başkenti"
|
|
inputs = tokenizer(text, return_tensors="pt")
|
|
outputs = model.generate(**inputs, max_new_tokens=20)
|
|
|
|
print(tokenizer.decode(outputs[0])) |