| | --- |
| | library_name: peft |
| | base_model: mistralai/Mistral-7B-v0.1 |
| | pipeline_tag: text-generation |
| | --- |
| | Description: Coding tasks in multiple languages\ |
| | Original dataset: https://huggingface.co/datasets/ise-uiuc/Magicoder-OSS-Instruct-75K \ |
| | ---\ |
| | 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) |
| | ``` |