New model from https://wandb.ai/wandb/huggingtweets/runs/1a3w2qxa
Browse files- README.md +26 -16
- config.json +5 -2
- flax_model.msgpack +0 -3
- pytorch_model.bin +2 -2
- tokenizer.json +0 -0
- tokenizer_config.json +1 -1
- training_args.bin +2 -2
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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- text: "My dream is"
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---
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<div>
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<div
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</div>
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I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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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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The model was trained on
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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 @rterdogan'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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- text: "My dream is"
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---
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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/1151410974240444416/yVvaD7hU_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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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">Recep Tayyip Erdoğan</div>
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<div style="text-align: center; font-size: 14px;">@rterdogan</div>
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</div>
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I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
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## Training data
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The model was trained on tweets from Recep Tayyip Erdoğan.
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| Data | Recep Tayyip Erdoğan |
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| --- | --- |
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| Tweets downloaded | 3250 |
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| Retweets | 418 |
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| Short tweets | 54 |
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| Tweets kept | 2778 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/wf1dbaih/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 @rterdogan's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1a3w2qxa) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1a3w2qxa/artifacts) is logged and versioned.
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## How to use
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config.json
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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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"n_inner": null,
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"n_layer": 12,
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"n_positions": 1024,
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"resid_pdrop": 0.1,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"top_p": 0.95
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}
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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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"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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"n_inner": null,
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"n_layer": 12,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"top_p": 0.95
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.19.4",
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"use_cache": true,
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"vocab_size": 50257
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}
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flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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size 497764120
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pytorch_model.bin
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size 510396521
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tokenizer.json
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tokenizer_config.json
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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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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "gpt2", "tokenizer_class": "GPT2Tokenizer"}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 3183
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