New model from https://wandb.ai/wandb/huggingtweets/runs/3jce6uxf
Browse files- README.md +8 -8
- config.json +1 -1
- pytorch_model.bin +2 -2
- tokenizer.json +8 -5
- training_args.bin +2 -2
README.md
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---
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language: en
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thumbnail:
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tags:
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- huggingtweets
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widget:
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@@ -42,20 +42,20 @@ The model was trained on tweets from jamar " The Fool β majima π΅πΈ.
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| Data | jamar " The Fool β majima π΅πΈ |
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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 @rxmaybike'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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| Data | jamar " The Fool β majima π΅πΈ |
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| --- | --- |
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| Tweets downloaded | 3047 |
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| Retweets | 1765 |
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| Short tweets | 332 |
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| Tweets kept | 950 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/ap206363/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 @rxmaybike's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3jce6uxf) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3jce6uxf/artifacts) is logged and versioned.
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## How to use
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config.json
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}
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},
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"torch_dtype": "float32",
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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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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.18.0",
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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.json
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"normalized": false,
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"special": true
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"model": {
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"type": "BPE",
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training_args.bin
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