初始化项目,由ModelHub XC社区提供模型
Model: huggingtweets/gladosystem Source: Original Platform
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README.md
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---
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language: en
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thumbnail: http://www.huggingtweets.com/gladosystem/1675702153306/predictions.png
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tags:
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- huggingtweets
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widget:
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- text: "My dream is"
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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:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1798039631/glados_by_upsidedownbattleship-d3fglhs_400x400.jpg')">
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</div>
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<div
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style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
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</div>
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<div
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style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
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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">🤖 AI BOT 🤖</div>
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<div style="text-align: center; font-size: 16px; font-weight: 800">GLaDOS</div>
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<div style="text-align: center; font-size: 14px;">@gladosystem</div>
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</div>
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I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
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## How does it work?
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The model uses the following pipeline.
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To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
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## Training data
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The model was trained on tweets from GLaDOS.
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| Data | GLaDOS |
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| --- | --- |
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| Tweets downloaded | 3250 |
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| Retweets | 0 |
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| Short tweets | 103 |
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| Tweets kept | 3147 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/hg8zi8b5/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
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## Training procedure
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The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @gladosystem's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/ouo7spgq) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/ouo7spgq/artifacts) is logged and versioned.
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## How to use
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You can use this model directly with a pipeline for text generation:
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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='huggingtweets/gladosystem')
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generator("My dream is", num_return_sequences=5)
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```
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## Limitations and bias
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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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In addition, the data present in the user's tweets further affects the text generated by the model.
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## About
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*Built by Boris Dayma*
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[](https://twitter.com/intent/follow?screen_name=borisdayma)
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For more details, visit the project repository.
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[](https://github.com/borisdayma/huggingtweets)
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config.json
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"_name_or_path": "gpt2",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"task_specific_params": {
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"temperature": 1.0,
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"top_p": 0.95
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.26.0",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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"_from_model_config": true,
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}
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"bos_token": "<|endoftext|>",
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version https://git-lfs.github.com/spec/v1
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