LLIMONIIE: Large Language Instructed Model for Open Named Italian Information Extraction
LLIMONIE generalizes IE across diverse domains without requiring input ontologies.
- Perform three tasks:
Open Named Entity Recognition
Open Relation Extraction
Joint Entity and Relation Extraction
💻 Quick Start
Setup conda environment
Install the unsloth package following the repo guide
Clone the repository
git clone https://github.com/leonardoPiano/LLIMONIE.git
Run the generation
from PromptTemplates.instruct_prompt_templates import NER,RE,JOINT
from LLM.Unsloth import UnslothLLM
model_path="leopiano98/LLIMONIIE_phi3-mini"
llimonie=UnslothLLM(model_path,inference=True)
task=NER
text="Alessandro Manzoni è considerato uno dei maggiori romanzieri italiani di tutti i tempi per il suo celebre romanzo I promessi sposi"
messages = [{"role": "system", "content": task},
{"role": "user", "content": text}]
output= llimonie.generate(messages, max_new_tokens=512)
#output: Alessandro Manzoni[Writer|Person]; I promessi sposi[Novel|Book]; italiani[Nationality|Ethnicity]
- Developed by: leopiano98
- License: apache-2.0
- Finetuned from model : Phi-3-mini-4k-instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for leopiano98/LLIMONIIE_phi3-mini
Base model
unsloth/Phi-3-mini-4k-instruct-bnb-4bit