# FineNeo: A simple way to finetune your very own GPT-Neo model.
> Created by Tekkonetes with debugging help from ChatGPT.
> @Tekkonetes (HuggingFace) / @pxlmastrXD (Replit)

So, you want to fine-tune a GPT-Neo model? Well, here's the simplest script you will get. It uses a text dataset to fine-tune, and it also will tune the model fairly quickly. Normally, it takes about 5 seconds for an epoch to finish, so here are some estimated times:
|Epochs|Time (Seconds)| Adjusted time
|--|--|--|
| 1 | 5 | |
| 10 | 50 | 
| 50 | 250 | 4m 10s
| 100 | 500 | 8m 20s

Yes, it's fairly fast. However, it depends on which GPT-Neo model you're fine-tuning. For example, the chart above is the `EleutherAI/GPT-Neo-125M` model. If you use the `Gpt-Neo-1.3B` model, it will probably take longer.

## Using the script.
First, download the `tune.py` file to your computer. Then (optional) set up a virtual environment:
```bash
python -m venv venv
source venv/bin/activate
```
Now, install the needed packages:
```bash
pip install transformers torch
```
Finally, create your dataset, modify the file to use the dataset, and run the python script.
```bash
python tune.py
```
Your model and tokenizer will appear in the `fine-tuned-gpt-neo` directory. You can then use transformers to run the model, or upload the files to the HuggingFace hub.

Best of luck!
    - Tekkonetes
    - @pxlmastrXD (Replit)
{"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["gpt2"], "pipeline_tag": "text-generation"}
transformers pytorch gpt_neo text-generation gpt2 en license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #gpt_neo #text-generation #gpt2 #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 

FineNeo: A simple way to finetune your very own GPT-Neo model.
==============================================================



> 
> Created by Tekkonetes with debugging help from ChatGPT.
> @Tekkonetes (HuggingFace) / @pxlmastrXD (Replit)
> 
> 
> 


So, you want to fine-tune a GPT-Neo model? Well, here's the simplest script you will get. It uses a text dataset to fine-tune, and it also will tune the model fairly quickly. Normally, it takes about 5 seconds for an epoch to finish, so here are some estimated times:


Epochs: 1, Time (Seconds): 5, Adjusted time: 
Epochs: 10, Time (Seconds): 50, Adjusted time: 
Epochs: 50, Time (Seconds): 250, Adjusted time: 4m 10s
Epochs: 100, Time (Seconds): 500, Adjusted time: 8m 20s


Yes, it's fairly fast. However, it depends on which GPT-Neo model you're fine-tuning. For example, the chart above is the 'EleutherAI/GPT-Neo-125M' model. If you use the 'Gpt-Neo-1.3B' model, it will probably take longer.


Using the script.
-----------------


First, download the 'URL' file to your computer. Then (optional) set up a virtual environment:


Now, install the needed packages:


Finally, create your dataset, modify the file to use the dataset, and run the python script.


Your model and tokenizer will appear in the 'fine-tuned-gpt-neo' directory. You can then use transformers to run the model, or upload the files to the HuggingFace hub.


Best of luck!
- Tekkonetes
- @pxlmastrXD (Replit)



TAGS
#transformers #pytorch #gpt_neo #text-generation #gpt2 #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #gpt_neo #text-generation #gpt2 #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 
