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--- |
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library_name: peft |
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base_model: mistralai/Mistral-7B-v0.1 |
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pipeline_tag: text-generation |
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--- |
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Description: Coding tasks in multiple languages\ |
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Original dataset: https://huggingface.co/datasets/ise-uiuc/Magicoder-OSS-Instruct-75K \ |
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---\ |
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \ |
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The adapter_category is STEM and the name is Code Generation (magicoder)\ |
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---\ |
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Sample input: Below is a programming problem, paired with a language in which the solution should be written. Write a solution in the provided that appropriately solves the programming problem.\n\n### Problem: |
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def strlen(string: str) -> int: |
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""" Return length of given string |
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>>> strlen('') |
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0 |
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>>> strlen('abc') |
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3 |
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""" |
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\n\n### Language: python\n\n### Solution: \ |
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---\ |
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Sample output: ```python |
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def strlen(string: str) -> int: |
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return len(string)```\ |
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---\ |
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Try using this adapter yourself! |
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``` |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_id = "mistralai/Mistral-7B-v0.1" |
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peft_model_id = "predibase/magicoder" |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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model.load_adapter(peft_model_id) |
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``` |
