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--- |
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license: mit |
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datasets: |
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- DarwinAnim8or/grug |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- grug |
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- caveman |
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- fun |
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--- |
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# GPT-Grug-125m |
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A finetuned version of [GPT-Neo-125M](https://huggingface.co./EleutherAI/gpt-neo-125M) on the 'grug' dataset. |
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A demo is available [here](https://huggingface.co./spaces/DarwinAnim8or/grug-chat) |
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NOTE: A larger, more capable version can be found [here](https://huggingface.co./DarwinAnim8or/GPT-Grug-355m) |
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# Training Procedure |
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This was trained on the 'grug' dataset, using the "HappyTransformers" library on Google Colab. |
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This model was trained for 4 epochs with learning rate 1e-2. |
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The notebook used to train has been included in this repo. |
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# Biases & Limitations |
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This likely contains the same biases and limitations as the original GPT-Neo-125M that it is based on, and additionally heavy biases from the grug datasets. |
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# Intended Use |
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This model is meant for fun, please do not take anything this caveman says seriously. |
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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("GPT-NEO", "DarwinAnim8or/gpt-grug-125m") |
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#Set generation settings: |
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from happytransformer import GENSettings |
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args_top_k = GENSettings(no_repeat_ngram_size=3, do_sample=True,top_k=50, temperature=0.7, max_length=50, early_stopping=False) |
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#Generate a response: |
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result = happy_gen.generate_text("""Person: "Hello grug" |
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Grug: "hello person" |
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### |
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Person: "how are you grug" |
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Grug: "grug doing ok. grug find many berry. good for tribe." |
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### |
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Person: "what does grug think of new spear weapon?" |
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Grug: "grug no like new spear weapon. grug stick bigger. spear too small, break easy" |
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### |
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Person: "what does grug think of football?" |
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Grug: \"""", args=args_top_k) |
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print(result) |
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print(result.text) |
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``` |