AlekseyKorshuk commited on
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huggingartists

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README.md ADDED
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+ ---
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+ language: en
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+ datasets:
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+ - huggingartists/6ix9ine
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+ tags:
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+ - huggingartists
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+ - lyrics
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+ - lm-head
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+ - causal-lm
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+ widget:
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+ - text: "I am"
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+ ---
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+
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+ <div class="inline-flex flex-col" style="line-height: 1.5;">
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+ <div class="flex">
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+ <div
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+ style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://images.genius.com/b2b164a7c6c02dd0843ad597df5dbf4b.1000x1000x1.png&#39;)">
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+ </div>
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+ </div>
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+ <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div>
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+ <div style="text-align: center; font-size: 16px; font-weight: 800">6ix9ine</div>
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+ <a href="https://genius.com/artists/6ix9ine">
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+ <div style="text-align: center; font-size: 14px;">@6ix9ine</div>
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+ </a>
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+ </div>
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+
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+ I was made with [huggingartists](https://github.com/AlekseyKorshuk/huggingartists).
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+
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+ Create your own bot based on your favorite artist with [the demo](https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb)!
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+
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+ ## How does it work?
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+
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+ To understand how the model was developed, check the [W&B report](https://wandb.ai/huggingartists/huggingartists/reportlist).
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+
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+ ## Training data
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+
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+ The model was trained on lyrics from 6ix9ine.
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+
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+ Dataset is available [here](https://huggingface.co/datasets/huggingartists/6ix9ine).
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+ And can be used with:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("huggingartists/6ix9ine")
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+ ```
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+
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+ [Explore the data](https://wandb.ai/huggingartists/huggingartists/runs/1ubrxjqi/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
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+
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+ ## Training procedure
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+
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+ The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on 6ix9ine's lyrics.
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+
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/huggingartists/huggingartists/runs/x99noxul) for full transparency and reproducibility.
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+
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+ At the end of training, [the final model](https://wandb.ai/huggingartists/huggingartists/runs/x99noxul/artifacts) is logged and versioned.
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+
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+ ## How to use
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+
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+ You can use this model directly with a pipeline for text generation:
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+
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+ ```python
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+ from transformers import pipeline
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+ generator = pipeline('text-generation',
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+ model='huggingartists/6ix9ine')
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+ generator("I am", num_return_sequences=5)
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+ ```
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+
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+ Or with Transformers library:
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelWithLMHead
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+
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+ tokenizer = AutoTokenizer.from_pretrained("huggingartists/6ix9ine")
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+
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+ model = AutoModelWithLMHead.from_pretrained("huggingartists/6ix9ine")
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+ ```
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+
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+ ## Limitations and bias
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+
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+ The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
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+
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+ In addition, the data present in the user's tweets further affects the text generated by the model.
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+
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+ ## About
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+
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+ *Built by Aleksey Korshuk*
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+
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+ [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk)
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+
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+ [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk)
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+
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+ [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky)
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+
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+ For more details, visit the project repository.
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+
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+ [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)
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