New model from https://wandb.ai/wandb/huggingtweets/runs/mouh8wiz

README.md

@@ -1,17 +1,27 @@
 ---
 language: en
-thumbnail: https://www.huggingtweets.com/vsshole/1614098988294/predictions.png
+thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
 tags:
 - huggingtweets
 widget:
 - text: "My dream is"
 ---
 
-<div>
-<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1012205185119088640/k1hzFM8u_400x400.jpg')">
-</div>
-<div style="margin-top: 8px; font-size: 19px; font-weight: 800">🌺 m ny 🐝🐙 🤖 AI Bot </div>
-<div style="font-size: 15px">@vsshole bot</div>
+<div class="inline-flex flex-col" style="line-height: 1.5;">
+    <div class="flex">
+        <div
+			style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1468028789317935116/SYCkEdg7_400x400.jpg&#39;)">
+        </div>
+        <div
+            style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
+        </div>
+        <div
+            style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
+        </div>
+    </div>
+    <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
+    <div style="text-align: center; font-size: 16px; font-weight: 800">🌺 m ny 🐝🐙</div>
+    <div style="text-align: center; font-size: 14px;">@vsshole</div>
 </div>
 
 I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
@@ -24,28 +34,28 @@ 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).
+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).
 
 ## Training data
 
-The model was trained on [@vsshole's tweets](https://twitter.com/vsshole).
+The model was trained on tweets from 🌺 m ny 🐝🐙.
 
-| Data | Quantity |
+| Data | 🌺 m ny 🐝🐙 |
 | --- | --- |
-| Tweets downloaded | 3208 |
-| Retweets | 294 |
-| Short tweets | 1597 |
-| Tweets kept | 1317 |
+| Tweets downloaded | 3231 |
+| Retweets | 409 |
+| Short tweets | 1475 |
+| Tweets kept | 1347 |
 
-[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/9puhkja4/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3piwpl9z/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 @vsshole's tweets.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/9ps1hg3p) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/mouh8wiz) for full transparency and reproducibility.
 
-At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/9ps1hg3p/artifacts) is logged and versioned.
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/mouh8wiz/artifacts) is logged and versioned.
 
 ## How to use
 

config.json

@@ -8,7 +8,6 @@
   "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",
@@ -18,7 +17,10 @@
   "n_inner": null,
   "n_layer": 12,
   "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
   "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
   "summary_activation": null,
   "summary_first_dropout": 0.1,
   "summary_proj_to_labels": true,
@@ -34,7 +36,8 @@
       "top_p": 0.95
     }
   },
-  "transformers_version": "4.3.2",
+  "torch_dtype": "float32",
+  "transformers_version": "4.13.0",
   "use_cache": true,
   "vocab_size": 50257
 }

flax_model.msgpack

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pytorch_model.bin

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+oid sha256:bf2eea5ee707595fa7bba4a3c651003014e3ee67f62c13737929920412fe7bf7
+size 510403817

tokenizer_config.json

@@ -1 +1 @@
-{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "name_or_path": "gpt2"}
+{"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"}

training_args.bin

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+size 2927