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--- |
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language: |
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- en |
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license: mit |
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pipeline_tag: text-generation |
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model-index: |
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- name: chef-gpt-en |
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results: [] |
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widget: |
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- text: 'ingredients>> salmon, lemon; recipe>>' |
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--- |
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# chef-gpt-en |
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Test the model [HERE](https://chef-gpt.streamlit.app/). |
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Fine-tuned GPT-2 for recipe generation. [This](https://www.kaggle.com/datasets/shuyangli94/food-com-recipes-and-user-interactions/data) is the dataset that it's trained on. |
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## Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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MODEL_ID = "auhide/chef-gpt-en" |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID) |
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chef_gpt = AutoModelForCausalLM.from_pretrained(MODEL_ID) |
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ingredients = ", ".join([ |
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"spaghetti", |
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"tomatoes", |
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"basel", |
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"salt", |
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"chicken", |
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]) |
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prompt = f"ingredients>> {ingredients}; recipe>>" |
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tokens = chef_gpt.tokenizer(prompt, return_tensors="pt") |
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recipe = chef_gpt.generate(**tokens, max_length=124) |
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print(recipe) |
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``` |
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Here is a sample result of the prompt: |
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```bash |
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ingredients>> spaghetti, tomatoes, basel, salt, chicken; recipe>>cook spaghetti according to package directions |
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meanwhile, place tomato slices and basel in a large pot with salted water and bring to a boil |
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reduce heat and |
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``` |