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--- |
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license: mit |
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datasets: |
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- DarwinAnim8or/greentext |
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language: |
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- en |
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tags: |
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- fun |
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- greentext |
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widget: |
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- text: ">be me" |
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example_title: "be me" |
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co2_eq_emissions: |
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emissions: 60 |
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source: "https://mlco2.github.io/impact/#compute" |
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training_type: "fine-tuning" |
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geographical_location: "Oregon, USA" |
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hardware_used: "1 T4, Google Colab" |
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--- |
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# GPT-Greentext-355m |
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A finetuned version of [GPT2-Medium](https://huggingface.co/gpt2-medium) on the 'greentext' dataset. (Linked above) |
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A demo is available [here](https://huggingface.co/spaces/DarwinAnim8or/GPT-Greentext-Playground) |
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The demo playground is recommended over the inference box on the right. |
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The largest model in this series is located here: [GPT-Greentext-1.5b](https://huggingface.co/DarwinAnim8or/GPT-Greentext-1.5b) |
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# Training Procedure |
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This was trained on the 'greentext' dataset, using the "HappyTransformers" library on Google Colab. |
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This model was trained for 15 epochs with learning rate 1e-2. |
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# Biases & Limitations |
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This likely contains the same biases and limitations as the original GPT2 that it is based on, and additionally heavy biases from the greentext dataset. |
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It likely will generate offensive output. |
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# Intended Use |
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This model is meant for fun, nothing else. |
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# Sample Use |
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```python |
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#Import model: |
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from happytransformer import HappyGeneration |
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happy_gen = HappyGeneration("GPT2", "DarwinAnim8or/GPT-Greentext-355m") |
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#Set generation settings: |
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from happytransformer import GENSettings |
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args_top_k = GENSettingsGENSettings(no_repeat_ngram_size=3, do_sample=True, top_k=80, temperature=0.8, max_length=150, early_stopping=False) |
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#Generate a response: |
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result = happy_gen.generate_text(""">be me |
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>""", args=args_top_k) |
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print(result) |
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print(result.text) |
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``` |
