New model from https://wandb.ai/wandb/huggingtweets/runs/dojoofh6
Browse files- README.md +9 -9
- config.json +1 -1
- generation_config.json +1 -1
- merges.txt +1 -1
- pytorch_model.bin +1 -1
- tokenizer.json +1 -0
- tokenizer_config.json +1 -2
- 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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<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/
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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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| Data | 🌞 |
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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 @raspberryl0ver'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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<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/1647023471749111810/G5s5jf4-_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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| Data | 🌞 |
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| --- | --- |
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| Tweets downloaded | 2241 |
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| Retweets | 457 |
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| Short tweets | 291 |
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| Tweets kept | 1493 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/btps6b16/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 @raspberryl0ver's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/dojoofh6) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/dojoofh6/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": "4.28.1",
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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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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.
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}
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.28.1"
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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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h e
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#version: 0.2
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Ġ t
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Ġ a
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h e
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pytorch_model.bin
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tokenizer.json
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"continuing_subword_prefix": "",
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"end_of_word_suffix": "",
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"fuse_unk": false,
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"vocab": {
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"!": 0,
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"\"": 1,
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"continuing_subword_prefix": "",
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"end_of_word_suffix": "",
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"fuse_unk": false,
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"byte_fallback": false,
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"vocab": {
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"!": 0,
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"\"": 1,
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"model_max_length": 1024,
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"name_or_path": "gpt2",
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"special_tokens_map_file": null,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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}
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{
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"add_prefix_space": false,
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"model_max_length": 1024,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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}
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training_args.bin
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