New model from https://wandb.ai/wandb/huggingtweets/runs/199ych58
Browse files- README.md +9 -9
- config.json +1 -0
- merges.txt +1 -1
- pytorch_model.bin +2 -2
- special_tokens_map.json +1 -1
- tokenizer_config.json +1 -1
- training_args.bin +1 -1
- vocab.json +0 -0
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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@@ -51,32 +51,32 @@ The model was trained on [@marknorm's tweets](https://twitter.com/marknorm).
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<tbody style='border-width:0'>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Tweets downloaded</td>
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<td style='border-width:0'>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Retweets</td>
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<td style='border-width:0'>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Short tweets</td>
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<td style='border-width:0'>
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</tr>
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<tr style='border-width:0'>
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<td style='border-width:0'>Tweets kept</td>
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<td style='border-width:0'>
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</tr>
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</tbody>
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</table>
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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 @marknorm'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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## Intended uses & limitations
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@@ -110,4 +110,4 @@ For more details, visit the project repository.
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[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
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<!--- random size file
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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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<tbody style='border-width:0'>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Tweets downloaded</td>
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<td style='border-width:0'>3208</td>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Retweets</td>
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<td style='border-width:0'>166</td>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Short tweets</td>
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<td style='border-width:0'>582</td>
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</tr>
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<tr style='border-width:0'>
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<td style='border-width:0'>Tweets kept</td>
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<td style='border-width:0'>2460</td>
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</tr>
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</tbody>
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</table>
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/c7f7hyql/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 @marknorm's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/199ych58) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/199ych58/artifacts) is logged and versioned.
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## Intended uses & limitations
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[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
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<!--- random size file -->
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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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"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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"use_cache": true,
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"vocab_size": 50257
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}
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merges.txt
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#version: 0.2
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Ġ t
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Ġ a
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#version: 0.2 - Trained by `huggingface/tokenizers`
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Ġ a
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h e
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed019b68eb3cc7ae665f213d9e05d77527cb66ac500ce46f4e044b26b0e9bb02
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size 510406560
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special_tokens_map.json
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{"bos_token":
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{"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}
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tokenizer_config.json
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{"
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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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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1775
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version https://git-lfs.github.com/spec/v1
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oid sha256:a338be97b210d4affda94ecb39787dd59cc25936fecfd5e7f198e56da24311f0
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size 1775
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vocab.json
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