gpt-fluentui-flat-svg

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+train/svg_flat.txt filter=lfs diff=lfs merge=lfs -text

config.json

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+{
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+  "torch_dtype": "float32",
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+  "use_cache": true,
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+}

pytorch_model.bin

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special_tokens_map.json

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+      "7 26",
+      "66 1",
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+      "A D",
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+      "77 9",
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+      "56 25",
+      "3 05",
+      "29 01",
+      "3 53",
+      "48 1",
+      "22 01",
+      "65 99",
+      "5 999",
+      "63 99",
+      "8 03",
+      "16 01",
+      "09 01",
+      "28 01",
+      "84 01",
+      "69 01",
+      "03 01",
+      "73 2",
+      "6 85",
+      "99 89",
+      "47 99",
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+      "25 88",
+      "328 4",
+      "11 99",
+      "67 01",
+      "18 01"
+    ]
+  }
+}

tokenizer_config.json

@@ -0,0 +1,8 @@
+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "<|endoftext|>"
+}

train/atg_train.py

@@ -0,0 +1,38 @@
+
+import os
+#os.environ["TOKENIZERS_PARALLELISM"] = "False"
+
+from aitextgen.tokenizers import train_tokenizer
+from aitextgen import aitextgen
+from aitextgen.utils import build_gpt2_config
+
+def train_atg_tokenizer():
+    train_tokenizer("svg_flat.txt", vocab_size=1000)
+
+def prepare_model():
+    config = build_gpt2_config(vocab_size=1000, max_length=4096, dropout=0.1, n_embd=768, n_layer=8, n_head=12)
+    ai = aitextgen(tokenizer_file="aitextgen.tokenizer.json", config=config)
+    ai.save_for_upload("./trained_model")
+
+def do_train():
+    ai = aitextgen(model_folder="./trained_model", tokenizer_file="aitextgen.tokenizer.json")
+    ai.train("svg_flat.txt", batch_size=1, num_steps=60000, save_every= 2500, fp16=False, generate_every=1000, learning_rate=0.001)
+    ai.train("svg_flat.txt", batch_size=1, num_steps=40000, save_every= 2500, fp16=False, generate_every=1000, learning_rate=0.0001)
+
+def do_sample():
+    ai = aitextgen(model_folder="./trained_model", tokenizer_file="./trained_model/tokenizer.json", to_gpu=True)
+    ai.generate(prompt="\n", max_length=4000,seed=42,do_sample=True)
+
+    # svg_file_header = "<svg width=\"32\" height=\"32\" viewBox=\"0 0 32 32\" fill=\"none\" xmlns=\"http://www.w3.org/2000/svg\">"
+    # TODO: Extract from generated output and into a seperate .svg file all sequences which starts with svg_file_header and ends with:
+    #  A. </svg>
+    #  B. If the sequence does not end with </svg> then find the last > in the sequence and append </svg> to it
+
+def main():
+    #train_atg_tokenizer()
+    #prepare_model()
+    #do_train()
+    do_sample()
+
+if __name__ == "__main__":
+    main()

train/svg_flat.txt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f59bd61fb40274fb3b58b36b5c623e0e9ab00a387c0a825e69b06e64f4dda433
+size 16615136