New model from https://wandb.ai/wandb/huggingtweets/runs/auuc2mv0
Browse files- README.md +37 -63
- added_tokens.json +1 -0
- config.json +16 -4
- merges.txt +0 -0
- pytorch_model.bin +2 -2
- special_tokens_map.json +1 -1
- tokenizer.json +0 -0
- tokenizer_config.json +1 -1
- training_args.bin +3 -0
- vocab.json +0 -0
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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- text: "My dream is"
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---
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<
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</
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<div style="
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<div style="
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<div style="font-size: 15px; color: #657786">@pabloiglesias bot</div>
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</div>
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I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
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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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<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'>3205</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'>1205</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'>186</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'>1814</td>
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</tr>
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</tbody>
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</table>
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[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/1vigwb74/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 @pabloiglesias'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://app.wandb.ai/wandb/huggingtweets/runs/37wvu3wl/artifacts) is logged and versioned.
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You can use this model directly with a pipeline for text generation:
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### Limitations and bias
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The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
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*Built by Boris Dayma*
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</section>
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[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](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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[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](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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- 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/1337047075859668992/vsS3FHEd_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">Pablo Iglesias 🔻</div>
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<div style="text-align: center; font-size: 14px;">@pabloiglesias</div>
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</div>
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I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
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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 Pablo Iglesias 🔻.
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| Data | Pablo Iglesias 🔻 |
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| --- | --- |
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| Tweets downloaded | 3230 |
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| Retweets | 1157 |
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| Short tweets | 191 |
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| Tweets kept | 1882 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1cxyib7q/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 @pabloiglesias's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/auuc2mv0) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/auuc2mv0/artifacts) is logged and versioned.
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## How to use
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You can use this model directly with a pipeline for text generation:
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```python
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from transformers import pipeline
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generator = pipeline('text-generation',
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model='huggingtweets/pabloiglesias')
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generator("My dream is", num_return_sequences=5)
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```
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## Limitations and bias
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The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
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*Built by Boris Dayma*
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[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)
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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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added_tokens.json
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{"<|endoftext|>": 52000}
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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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],
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"attn_pdrop": 0.1,
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"bos_token_id":
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"embd_pdrop": 0.1,
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"eos_token_id":
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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_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer":
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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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{
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"_name_or_path": "mrm8488/GuaPeTe-2-tiny-finetuned-TED",
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"_num_labels": 1,
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 0,
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"embd_pdrop": 0.1,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"id2label": {
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"0": "LABEL_0"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0
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},
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer": 6,
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"n_positions": 1024,
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"resid_pdrop": 0.1,
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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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"transformers_version": "4.6.0",
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"use_cache": true,
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"vocab_size": 52001
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 339333191
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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.json
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tokenizer_config.json
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{"
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{"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, "max_len": 1024, "special_tokens_map_file": "/root/.cache/huggingface/transformers/cc4a7c4d36692dc96a2645ce7c3039a9d2976ffb22d8d42e10771d45cca07151.3ae9ae72462581d20e36bc528e9c47bb30cd671bb21add40ca0b24a0be9fac22", "name_or_path": "mrm8488/GuaPeTe-2-tiny-finetuned-TED", "errors": "replace"}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 2479
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vocab.json
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