New model from https://wandb.ai/wandb/huggingtweets/runs/1qkvoxvy
Browse files- README.md +11 -11
- config.json +1 -1
- pytorch_model.bin +2 -2
- special_tokens_map.json +5 -1
- tokenizer.json +6 -3
- tokenizer_config.json +10 -1
- training_args.bin +2 -2
README.md
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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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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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</div>
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
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<div style="text-align: center; font-size: 16px; font-weight: 800"
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<div style="text-align: center; font-size: 14px;">@gaucheian</div>
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</div>
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## Training data
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The model was trained on tweets from
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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 @gaucheian'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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<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/1538913438189371394/Fho4_Laq_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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</div>
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</div>
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
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<div style="text-align: center; font-size: 16px; font-weight: 800">-_______-</div>
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<div style="text-align: center; font-size: 14px;">@gaucheian</div>
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</div>
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## Training data
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The model was trained on tweets from -_______-.
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| Data | -_______- |
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| --- | --- |
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| Tweets downloaded | 3047 |
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| Retweets | 161 |
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| Short tweets | 307 |
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| Tweets kept | 2579 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/26ot4z4p/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 @gaucheian's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1qkvoxvy) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1qkvoxvy/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": "4.20.1",
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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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special_tokens_map.json
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{
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{
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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tokenizer.json
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"pre_tokenizer": {
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"type": "ByteLevel",
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"add_prefix_space": false,
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"trim_offsets": true
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"post_processor": {
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"decoder": {
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"add_prefix_space": true,
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"trim_offsets": true
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"model": {
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"type": "BPE",
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"pre_tokenizer": {
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"type": "ByteLevel",
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"trim_offsets": true,
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"use_regex": true
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"add_prefix_space": true,
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"trim_offsets": false,
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"use_regex": true
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"decoder": {
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"type": "ByteLevel",
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"add_prefix_space": true,
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"trim_offsets": true,
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"use_regex": true
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"model": {
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"type": "BPE",
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tokenizer_config.json
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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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training_args.bin
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