Instructions to use Luca0867/complexity_evolved_selfinstruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luca0867/complexity_evolved_selfinstruct with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Luca0867/complexity_evolved_selfinstruct", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -20,7 +20,7 @@ It has been trained using [TRL](https://github.com/huggingface/trl).
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from transformers import pipeline
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question = "Write a Python function to implement insertion sort on a list of floating-point numbers and return the sorted list."
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generator = pipeline("text-generation", model="Luca0867/complexity_evolved_selfinstruct"
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output = generator([{"role": "user", "content": question}], max_new_tokens=1024, return_full_text=False)[0]
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print(output["generated_text"])
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from transformers import pipeline
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question = "Write a Python function to implement insertion sort on a list of floating-point numbers and return the sorted list."
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generator = pipeline("text-generation", model="Luca0867/complexity_evolved_selfinstruct")
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output = generator([{"role": "user", "content": question}], max_new_tokens=1024, return_full_text=False)[0]
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print(output["generated_text"])
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