New model from https://wandb.ai/wandb/huggingtweets/runs/2bbb0r1k
Browse files- README.md +11 -9
- config.json +2 -0
- pytorch_model.bin +2 -2
- tokenizer_config.json +1 -1
- training_args.bin +3 -0
README.md
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---
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language: en
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thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/
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tags:
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- huggingtweets
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widget:
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<section class='prose'>
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<div>
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<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Chris Van Pelt (CVP) 🤖 AI Bot </div>
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<div style="font-size: 15px; color: #657786">@vanpelt bot</div>
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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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<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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</tbody>
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</table>
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[Explore the data](https://
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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 @vanpelt's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://
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At the end of training, [the final model](https://
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## Intended uses & limitations
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</section>
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[](https://twitter.com/borisdayma)
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<section class='prose'>
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For more details, visit the project repository.
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</section>
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[](https://github.com/borisdayma/huggingtweets)
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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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<section class='prose'>
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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/995187395531161601/4mrM2flB_400x400.jpg')">
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Chris Van Pelt (CVP) 🤖 AI Bot </div>
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<div style="font-size: 15px; color: #657786">@vanpelt bot</div>
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To understand how the model was developed, check the [W&B report](https://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).
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## Training data
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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'>813</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'>87</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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</tbody>
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</table>
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2hewg8ge/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 @vanpelt's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2bbb0r1k) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2bbb0r1k/artifacts) is logged and versioned.
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## Intended uses & limitations
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</section>
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[](https://twitter.com/intent/follow?screen_name=borisdayma)
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<section class='prose'>
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For more details, visit the project repository.
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</section>
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[](https://github.com/borisdayma/huggingtweets)
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<!--- random size file -->
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config.json
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{
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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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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{
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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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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"gradient_checkpointing": false,
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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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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:ddd934438e6f80239000fa7b096c9a12fb3c6a4125d95c6f35cde3d3ddc67bd4
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size 510406692
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tokenizer_config.json
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{"model_max_length": 1024}
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{"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "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 sha256:9dbce1b448de71ee77aa06afa1d11a183dba0cae433b3a475ccbcbc704a6a56e
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size 1775
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