| library_name: peft | |
| base_model: mistralai/Mistral-7B-v0.1 | |
| pipeline_tag: text-generation | |
| Description: Coding tasks in multiple languages\ | |
| Original dataset: magicoder \ | |
| ---\ | |
| Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \ | |
| The adapter_category is STEM and the name is Code Generation (magicoder)\ | |
| ---\ | |
| 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: | |
| def strlen(string: str) -> int: | |
| """ Return length of given string | |
| >>> strlen('') | |
| 0 | |
| >>> strlen('abc') | |
| 3 | |
| """ | |
| \n\n### Language: python\n\n### Solution: \ | |
| ---\ | |
| Sample output: ```python | |
| def strlen(string: str) -> int: | |
| return len(string) | |
| ```\ | |
| ---\ | |
| Try using this adapter yourself! | |
| ``` | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model_id = "mistralai/Mistral-7B-v0.1" | |
| peft_model_id = "predibase/magicoder" | |
| model = AutoModelForCausalLM.from_pretrained(model_id) | |
| model.load_adapter(peft_model_id) | |
| ``` |