New model from https://wandb.ai/wandb/huggingtweets/runs/3q94y8me

README.md

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+---
+language: en
+thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
+tags:
+- huggingtweets
+widget:
+- text: "My dream is"
+---
+
+<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
+
+<style>
+@media (prefers-color-scheme: dark) {
+  .prose { color: #E2E8F0 !important; }
+  .prose h2, .prose h3, .prose a, .prose thead { color: #F7FAFC !important; }
+}
+</style>
+
+<section class='prose'>
+
+<div>
+<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/953263245678215168/gKWkzY_f_400x400.jpg')">
+</div>
+<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Nathan Law 羅冠聰 😷 🤖 AI Bot </div>
+<div style="font-size: 15px; color: #657786">@nathanlawkc bot</div>
+</div>
+
+I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
+
+Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
+
+## How does it work?
+
+The model uses the following pipeline.
+
+![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
+
+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).
+
+## Training data
+
+The model was trained on [@nathanlawkc's tweets](https://twitter.com/nathanlawkc).
+
+<table style='border-width:0'>
+<thead style='border-width:0'>
+<tr style='border-width:0 0 1px 0; border-color: #CBD5E0'>
+<th style='border-width:0'>Data</th>
+<th style='border-width:0'>Quantity</th>
+</tr>
+</thead>
+<tbody style='border-width:0'>
+<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
+<td style='border-width:0'>Tweets downloaded</td>
+<td style='border-width:0'>2786</td>
+</tr>
+<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
+<td style='border-width:0'>Retweets</td>
+<td style='border-width:0'>996</td>
+</tr>
+<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
+<td style='border-width:0'>Short tweets</td>
+<td style='border-width:0'>463</td>
+</tr>
+<tr style='border-width:0'>
+<td style='border-width:0'>Tweets kept</td>
+<td style='border-width:0'>1327</td>
+</tr>
+</tbody>
+</table>
+
+[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3svb5x6n/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+
+## Training procedure
+
+The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @nathanlawkc's tweets.
+
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3q94y8me) for full transparency and reproducibility.
+
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3q94y8me/artifacts) is logged and versioned.
+
+## Intended uses & limitations
+
+### How to use
+
+You can use this model directly with a pipeline for text generation:
+
+<pre><code><span style="color:#03A9F4">from</span> transformers <span style="color:#03A9F4">import</span> pipeline
+generator = pipeline(<span style="color:#FF9800">'text-generation'</span>,
+                     model=<span style="color:#FF9800">'huggingtweets/nathanlawkc'</span>)
+generator(<span style="color:#FF9800">"My dream is"</span>, num_return_sequences=<span style="color:#8BC34A">5</span>)</code></pre>
+
+
+### Limitations and bias
+
+The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
+
+In addition, the data present in the user's tweets further affects the text generated by the model.
+
+## About
+
+*Built by Boris Dayma*
+
+</section>
+
+[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)
+
+<section class='prose'>
+For more details, visit the project repository.
+</section>
+
+[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)

config.json

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+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "gradient_checkpointing": false,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "resid_pdrop": 0.1,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 160,
+      "min_length": 10,
+      "prefix": "<|endoftext|>",
+      "temperature": 1.0,
+      "top_p": 0.95
+    }
+  },
+  "use_cache": true,
+  "vocab_size": 50257
+}

pytorch_model.bin

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special_tokens_map.json

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+{"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}

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"}

training_args.bin

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