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--- |
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title: "WSB-GPT-7B Quantized in GGUF" |
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tags: |
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- GGUF |
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language: en |
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--- |
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# Tsunemoto GGUF's of WSB-GPT-7B |
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This is a GGUF quantization of WSB-GPT-7B. |
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## Original Repo Link: |
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[Original Repository](https://huggingface.co/Sentdex/WSB-GPT-7B) |
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## Original Model Card: |
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--- |
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# Model Card for WSB-GPT-7B |
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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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### Model Description |
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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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- **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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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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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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## Bias, Risks, and Limitations |
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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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Just be advised this model can be offensive and is not intended for all audiences! |
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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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### Comment: |
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[parent comment text] |
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### REPLY: |
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[bot's reply] |
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### END. |
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``` |
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Use the code below to get started with the model. |
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```py |
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from transformers import pipeline |
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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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# Define your prompt |
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prompt = """### Comment: |
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How does the stock market actually work? |
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### REPLY: |
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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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# 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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Example continued generation from above: |
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``` |
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### Comment: |
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How does the stock market actually work? |
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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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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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#### Hardware |
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This QLoRA was trained on a Lambda Labs 1x H100 80GB GPU instance. |
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## Citation |
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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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## Model Card Contact |
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harrison@pythonprogramming.net |
