This is a Llama 2 7B Chat model fine-tuned with QLoRA on 2017-2018ish /r/wallstreetbets subreddit comments and responses, with the hopes of learning more about QLoRA and creating models with a little more character.
Language(s) (NLP): Multilingual from Llama 2, but not sure what the fine-tune did to it, or if the fine-tuned behavior translates well to other languages. Let me know!
License: Apache 2.0
Finetuned from Llama 2 7B Chat
Demo [optional]: [More Information Needed]
Uses
This model's primary purpose is to be a fun chatbot and to learn more about QLoRA. It is not intended to be used for any other purpose and some people may find it abrasive/offensive.
Bias, Risks, and Limitations
This model is prone to using at least 3 words that were popularly used in the WSB subreddit in that era that are much more frowned-upon. As time goes on, I may wind up pruning or find-replacing these words in the training data, or leaving it.
Just be advised this model can be offensive and is not intended for all audiences!
1from transformers import pipeline
23# Initialize the pipeline for text generation using the Sentdex/WSB-GPT-7B model4pipe = pipeline("text-generation", model="Sentdex/WSB-GPT-7B")56# Define your prompt7prompt ="""### Comment:
8How does the stock market actually work?
910### REPLY:
11"""1213# Generate text based on the prompt14generated_text = pipe(prompt, max_length=128, num_return_sequences=1)1516# Extract and print the generated text17print(generated_text[0]['generated_text'].split("### END.")[0])
Example continued generation from above:
### Comment:
How does the stock market actually work?
### REPLY:
You sell when you are up and buy when you are down.
Despite </s> being the typical Llama stop token, I was never able to get this token to be generated in training/testing so the model would just never stop generating. I wound up testing with ### END. and that worked, but obviously isn't ideal. Will fix this in the future maybe(tm).
Hardware
This QLoRA was trained on a Lambda Labs 1x H100 80GB GPU instance.
