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Model: lvwerra/gpt2-imdb
Source: Original Platform

.gitattributes

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+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text

README.md

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+# GPT2-IMDB
+
+## What is it?
+A GPT2 (`gpt2`) language model fine-tuned on the [IMDB dataset](https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews).
+
+## Training setting
+
+The GPT2 language model was fine-tuned for 1 epoch on the IMDB dataset. All comments were joined into a single text file separated by the EOS token:
+
+```
+import pandas as pd
+df = pd.read_csv("imdb-dataset.csv")
+imdb_str = " <|endoftext|> ".join(df['review'].tolist())
+
+with open ('imdb.txt', 'w') as f:
+    f.write(imdb_str)
+```
+
+To train the model the `run_language_modeling.py` script in the `transformer` library was used:
+
+```
+python run_language_modeling.py 
+	--train_data_file imdb.txt 
+	--output_dir gpt2-imdb 
+	--model_type gpt2 
+	--model_name_or_path gpt2
+```

config.json

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+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "output_past": true,
+  "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,
+  "vocab_size": 50257
+}

flax_model.msgpack

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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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+{"max_len": 1024}

training_args.bin

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