language:
- en
tags:
- pytorch
- causal-lm
license: mit
Literature-7B-16384 - A Large Fine-tuned Model For Lengthy Fictional Storytelling
Literature-7B-16384 is a GPT-NeoX 7B model fine-tuned on 2GB of a diverse range of light novels, erotica, and annotated literature for the purpose of generating novel-like fictional text.
Model Description
The model used for fine-tuning is RedPajama-7B-16384, which is a 7 billion parameter auto-regressive language model finetuned with a 16384 token context window.
Training Data & Annotative Prompting
The data used in fine-tuning has been gathered from various sources such as the Gutenberg Project. The annotated fiction dataset has prepended tags to assist in generating towards a particular style. Here is an example prompt that shows how to use the annotations.
[ Title: The Dunwich Horror; Author: H. P. Lovecraft; Genre: Horror; Tags: 3rdperson, scary; Style: Dark ]
***
When a traveler in north central Massachusetts takes the wrong fork...
The annotations can be mixed and matched to help generate towards a specific style.
Downstream Uses
This model can be used for entertainment purposes and as a creative writing assistant for fiction writers.
Example Code
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained('hakurei/Literature-7B-16384')
tokenizer = AutoTokenizer.from_pretrained('hakurei/Literature-7B-16384')
prompt = '''[ Title: The Dunwich Horror; Author: H. P. Lovecraft; Genre: Horror ]
***
When a traveler'''
input_ids = tokenizer.encode(prompt, return_tensors='pt')
output = model.generate(input_ids, do_sample=True, temperature=1.0, top_p=0.9, repetition_penalty=1.2, max_length=len(input_ids[0])+100, pad_token_id=tokenizer.eos_token_id)
generated_text = tokenizer.decode(output[0])
print(generated_text)
An example output from this code produces a result that will look similar to:
[ Title: The Dunwich Horror; Author: H. P. Lovecraft; Genre: Horror ]
***
When a traveler comes to an unknown region, his thoughts turn inevitably towards the old gods and legends which cluster around its appearance. It is not that he believes in them or suspects their reality—but merely because they are present somewhere else in creation just as truly as himself, and so belong of necessity in any landscape whose features cannot be altogether strange to him. Moreover, man has been prone from ancient times to brood over those things most connected with the places where he dwells. Thus the Olympian deities who ruled Hyper
Team members and Acknowledgements
- Anthony Mercurio: Training
- 11b: Long Context
- Imperishable_NEET: Dataset