Downloads · 30 days
107
2% of all-time downloads
predibase/e2e_nlg
e2e_nlg is a text generation model from predibase. Use it when you need the model to write or continue text. It is set up for peft.
Description: Translation from meaning representation to natural language\ Original dataset: https://huggingface.co/datasets/e2enlg \ ---\ Try querying this adapter for free in Lora Land at https://predibase.com/lora-l…
Downloads · 30 days
107
2% of all-time downloads
All-time downloads
5.8K
Public
Repo size
13.6 MB
Likes
2
Public
Click a slice to open those files.
.safetensors13.6 MB · 100%
From the Hugging Face model README
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)