--- license: apache-2.0 datasets: - Sentdex/wsb_reddit_v002 --- # Model Card for WSB-GPT-13B This is a Llama 2 13B 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. ### Model Description - **Developed by:** Sentdex - **Shared by:** Sentdex - **GPU Compute provided by:** [Lambda Labs](https://lambdalabs.com/service/gpu-cloud) - **Model type:** Instruct/Chat - **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 13B 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! ## How to Get Started with the Model ### Prompt Format: ``` ### Comment: [parent comment text] ### REPLY: [bot's reply] ### END. ``` Use the code below to get started with the model. ```py from transformers import pipeline # Initialize the pipeline for text generation using the Sentdex/WSB-GPT-13B model pipe = pipeline("text-generation", model="Sentdex/WSB-GPT-13B") # Define your prompt prompt = """### Comment: How does the stock market actually work? ### REPLY: """ # Generate text based on the prompt generated_text = pipe(prompt, max_length=128, num_return_sequences=1) # Extract and print the generated text print(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 `` 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. ## Citation - Llama 2 (Meta AI) for the base model. - Farouk E / Far El: https://twitter.com/far__el for helping with all my silly questions about QLoRA - Lambda Labs for the compute. The model itself only took a few hours to train, but it took me days to learn how to tie everything together. - Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer for QLoRA + implementation on github: https://github.com/artidoro/qlora/ - @eugene-yh and @jinyongyoo on Github + @ChrisHayduk for the QLoRA merge: https://gist.github.com/ChrisHayduk/1a53463331f52dca205e55982baf9930 ## Model Card Contact harrison@pythonprogramming.net