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+ WSB-GPT-7B_Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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+ WSB-GPT-7B_Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - Sentdex/wsb_reddit_v002
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+ ---
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+
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+ # Model Card for WSB-GPT-7B
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+
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+ 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.
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+
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+
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+ ### Model Description
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+
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+ - **Developed by:** Sentdex
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+ - **Shared by:** Sentdex
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+ - **GPU Compute provided by:** [Lambda Labs](https://lambdalabs.com/service/gpu-cloud)
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+
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+ - **Model type:** Instruct/Chat
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+ - **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!
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+ - **License:** Apache 2.0
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+ - **Finetuned from Llama 2 7B Chat**
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+
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+
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ 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.
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+
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+ ## Bias, Risks, and Limitations
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+
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+ 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.
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+
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+ Just be advised this model can be offensive and is not intended for all audiences!
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+
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+ ## How to Get Started with the Model
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+ ### Prompt Format:
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+
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+ ```
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+ ### Comment:
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+ [parent comment text]
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+
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+ ### REPLY:
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+ [bot's reply]
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+
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+ ### END.
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+ ```
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+
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+ Use the code below to get started with the model.
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+
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+ ```py
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+ from transformers import pipeline
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+
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+ # Initialize the pipeline for text generation using the Sentdex/WSB-GPT-7B model
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+ pipe = pipeline("text-generation", model="Sentdex/WSB-GPT-7B")
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+
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+ # Define your prompt
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+ prompt = """### Comment:
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+ How does the stock market actually work?
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+
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+ ### REPLY:
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+ """
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+
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+ # Generate text based on the prompt
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+ generated_text = pipe(prompt, max_length=128, num_return_sequences=1)
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+
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+ # Extract and print the generated text
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+ print(generated_text[0]['generated_text'].split("### END.")[0])
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+ ```
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+
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+ Example continued generation from above:
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+
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+ ```
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+ ### Comment:
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+ How does the stock market actually work?
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+
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+ ### REPLY:
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+ You sell when you are up and buy when you are down.
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+ ```
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+
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+ 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).
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+
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+ #### Hardware
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+
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+ This QLoRA was trained on a Lambda Labs 1x H100 80GB GPU instance.
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+
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+ ## Citation
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+
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+ - Llama 2 (Meta AI) for the base model.
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+ - Farouk E / Far El: https://twitter.com/far__el for helping with all my silly questions about QLoRA
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+ - 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.
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+ - Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer for QLoRA + implementation on github: https://github.com/artidoro/qlora/
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+ - @eugene-yh and @jinyongyoo on Github + @ChrisHayduk for the QLoRA merge: https://gist.github.com/ChrisHayduk/1a53463331f52dca205e55982baf9930
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+
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+
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+ ## Model Card Contact
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+
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+
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+ ***
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+
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+ Vanilla Quantization by [nold](https://huggingface.co/nold), Model by [WSB-GPT-7B](https://huggingface.co/Sentdex/WSB-GPT-7B)
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