
### Fine tuned GPT Neo 125M with Sinhala Wikipedia Dataset

This model is fine tuned with acrticles from Sinhala Wikipedia [Dataset](https://dumps.wikimedia.org/siwiki/20230201/) for Sinhala text generation. Only the articles with word count in between 60 and 500 were used here.

### How to use

You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:

```py
>>> from transformers import pipeline
>>> generator = pipeline('text-generation', model='Suchinthana/sinhala-gpt-neo-siwiki')
>>> generator("නිර්මාණය කිරීම සඳහා ", do_sample=True, max_length=500)
```
{"language": ["si"], "license": "mit", "datasets": ["wikipedia"], "widget": [{"text": "\u0db6\u0dcf\u0dc4\u0dd2\u0dbb \u0db6\u0dd0\u0da7\u0dbb\u0dd2"}, {"text": "\u0db4\u0dd2\u0dbb\u0dd2\u0dc3\u0dd2\u0daf\u0dd4 \u0db4\u0dcf\u0db1\u0dd3\u0dba \u0da2\u0dbd\u0dba"}, {"text": "\u0db4\u0dbb\u0dd2\u0d9a\u0dca\u0dc2\u0dab\u0dba \u0db7\u0dcf\u0dc0\u0dd2\u0dad\u0dcf \u0d9a\u0dbb\u0db1 \u0dc0\u0dd2\u0daf\u0dca\u200d\u0dba\u0dcf\u0da5\u0dba\u0db1\u0dca"}], "pipeline_tag": "text-generation"}
transformers pytorch safetensors gpt_neo text-generation si dataset:wikipedia license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #gpt_neo #text-generation #si #dataset-wikipedia #license-mit #autotrain_compatible #endpoints_compatible #region-us 


### Fine tuned GPT Neo 125M with Sinhala Wikipedia Dataset

This model is fine tuned with acrticles from Sinhala Wikipedia Dataset for Sinhala text generation. Only the articles with word count in between 60 and 500 were used here.

### How to use

You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:


### Fine tuned GPT Neo 125M with Sinhala Wikipedia Dataset

This model is fine tuned with acrticles from Sinhala Wikipedia Dataset for Sinhala text generation. Only the articles with word count in between 60 and 500 were used here. ### How to use

You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
TAGS
#transformers #pytorch #safetensors #gpt_neo #text-generation #si #dataset-wikipedia #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Fine tuned GPT Neo 125M with Sinhala Wikipedia Dataset

This model is fine tuned with acrticles from Sinhala Wikipedia Dataset for Sinhala text generation. Only the articles with word count in between 60 and 500 were used here. ### How to use

You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
TAGS
#transformers #pytorch #safetensors #gpt_neo #text-generation #si #dataset-wikipedia #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Fine tuned GPT Neo 125M with Sinhala Wikipedia Dataset

This model is fine tuned with acrticles from Sinhala Wikipedia Dataset for Sinhala text generation. Only the articles with word count in between 60 and 500 were used here.### How to use

You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run: