peft safetensors text-generation base_model:mistralai/Mistral-7B-v0.1 base_model:adapter:mistralai/Mistral-7B-v0.1 region:us
---
base_model: mistralai/Mistral-7B-v0.1
library_name: peft
pipeline_tag: text-generation
---
Description: Translation from meaning representation to natural language\
Original dataset: https://huggingface.co/datasets/e2e_nlg \
---\
Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
The adapter_category is Structured-to-Text and the name is Structured-to-Text (e2e_nlg)\
---\
Sample input: You are given a meaning representation below. Please translate it into plain English. Here is an example:\n\n### Meaning Representation: name[Blue Spice], eatType[coffee shop], area[city centre]\n\n### Plain English: A coffee shop in the city centre area called Blue Spice.\n\nNow please translate the following meaning representation:\n\n### Meaning Representation: name[Blue Spice], eatType[pub], food[Chinese], area[city centre], familyFriendly[yes], near[Rainbow Vegetarian Café]\n\n### Plain English:\
---\
Sample output: Blue Spice is a pub that serves Chinese food. It is located in the city centre near Rainbow Vegetarian Café.\
---\
Try using this adapter yourself!
```
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "predibase/e2e_nlg"

model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)
```