New model from https://wandb.ai/wandb/huggingtweets/runs/ndb8e5s3
Browse files- README.md +10 -10
- config.json +1 -1
- pytorch_model.bin +1 -1
- tokenizer_config.json +1 -1
- training_args.bin +2 -2
README.md
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---
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language: en
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thumbnail: https://
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tags:
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- huggingtweets
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widget:
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---
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<div>
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<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Eel Enthusiast 🤖 AI Bot </div>
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<div style="font-size: 15px">@cheascake bot</div>
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![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
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To understand how the model was developed, check the [W&B report](https://
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## Training data
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| Data | Quantity |
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| --- | --- |
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| Tweets downloaded |
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| Retweets |
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| Short tweets |
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| Tweets kept |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/
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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 @cheascake's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/
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## How to use
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---
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language: en
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thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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tags:
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- huggingtweets
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widget:
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---
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<div>
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<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1378827669790461953/GLEmzCyo_400x400.jpg')">
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Eel Enthusiast 🤖 AI Bot </div>
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<div style="font-size: 15px">@cheascake bot</div>
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![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
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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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| Data | Quantity |
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| --- | --- |
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| Tweets downloaded | 3248 |
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| Retweets | 216 |
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| Short tweets | 732 |
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| Tweets kept | 2300 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1pgthrar/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 @cheascake's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/ndb8e5s3) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/ndb8e5s3/artifacts) is logged and versioned.
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## How to use
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config.json
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"top_p": 0.95
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}
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},
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 50257
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}
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"top_p": 0.95
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}
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},
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"transformers_version": "4.4.2",
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"use_cache": true,
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"vocab_size": 50257
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}
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pytorch_model.bin
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tokenizer_config.json
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "name_or_path": "gpt2"}
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "gpt2"}
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training_args.bin
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size 2287
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