---
license: mit
datasets:
- chloeliu/reddit_nosleep_posts
language:
- en
tags:
- fun
- horror
- writing
widget:
- text: "[WP] We don't go to ravenholm anymore [RESPONSE] "
  example_title: "[WP] We don't go to ravenholm anymore [RESPONSE] "
co2_eq_emissions:
  emissions: 60
  source: "https://mlco2.github.io/impact/#compute"
  training_type: "fine-tuning"
  geographical_location: "Oregon, USA"
  hardware_used: "1 T4, Google Colab"
---

# GPT-NoSleep-355m
A finetuned version of [GPT2-Medium](https://huggingface.co/gpt2-medium) on the 'reddit-nosleep-posts' dataset. (Linked above)

**TIP** You can find a larger, more capable version of the model here: [GPT-NoSleep-1.5b](https://huggingface.co/DarwinAnim8or/GPT-NoSleep-1.5b)

# Training Procedure
This was trained on the 'reddt-nosleep-posts' dataset, using the "HappyTransformers" library on Google Colab.
This model was trained for X epochs with learning rate 1e-2.

# Biases & Limitations
This likely contains the same biases and limitations as the original GPT2 that it is based on, and additionally heavy biases from the dataset.
It likely will generate offensive output. 

# Intended Use
This model is meant for fun, nothing else.

# Sample code
```python
#Import model:
from happytransformer import HappyGeneration
happy_gen = HappyGeneration("GPT2", "DarwinAnim8or/GPT-NoSleep-355m")

#Set generation settings:
from happytransformer import GENSettings
args_top_k = GENSettingsGENSettings(no_repeat_ngram_size=3, do_sample=True, top_k=80, temperature=0.8, max_length=150, early_stopping=False)

#Generate a response:
result = happy_gen.generate_text("[WP] We don't go to the forest at night [RESPONSE] ", args=args_top_k)

print(result)
print(result.text)
```