|
--- |
|
|
|
language: |
|
- "ur" |
|
license: "mit" |
|
datasets: |
|
- "Urdu-news-dataset" |
|
|
|
--- |
|
|
|
|
|
# GPT-2 |
|
|
|
|
|
Pretrained model on Urdu news la using a causal language modeling (CLM) objective. |
|
|
|
### How to use |
|
|
|
You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we |
|
set a seed for reproducibility: |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("Imran1/gpt2-urdu-news") |
|
|
|
model = AutoModelForCausalLM.from_pretrained("Imran1/gpt2-urdu-news") |
|
``` |
|
## Training data |
|
I fine tune gpt2 for downstream task like text generation, only for 1000 sample so it may not be good so. Due to resources limitation. |
|
|
|
|
|
## Evaluation results |
|
training loss 3.042 |
|
|
