Model Card for Model ID
This model is useful in the pipeline of complex information extraction. The model will generate discourse trees from complex sentences. Discourse trees contain simple split sentences and relationship between these sentences.
Model Details
Model Description
This model is useful in the pipeline of complex information extraction. The model will generate discourse trees from complex sentences. Discourse trees contain simple split sentences and relationship between these sentences.
- Developed by: BITS Hyderabad
- Model type: Language model
- Language(s) (NLP): English
- Finetuned from model [optional]: flan-t5-base
Uses
Direct Use
Model is finetuned and can directly be used.
[More Information Needed]
Recommendations
How to Get Started with the Model
Use the code below to get started with the model.
# If using Google Colab, login to HuggingFace is needed. Doing the following will prompt to enter the access token
# which can be obtained from Settings > AccessTokens
from huggingface_hub import notebook_login
notebook_login()
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import spacy
tokenizer = AutoTokenizer.from_pretrained("bphclegalie/t5-base-legen", token = True)
model = AutoModelForSeq2SeqLM.from_pretrained("bphclegalie/t5-base-legen", token = True)
nlp = spacy.load("en_core_web_sm")
def get_discourse_tree(text):
sentences = " ".join([t.text for t in nlp(text)])
input_ids = tokenizer(text, max_length=384, truncation=True, return_tensors="pt").input_ids
outputs = model.generate(input_ids=input_ids, max_length=128)
answer = [tokenizer.decode(output, skip_special_tokens = True) for output in outputs]
return " ".join(answer)
[More Information Needed]
Training Details
Training Data
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Glossary [optional]
[More Information Needed]
More Information [optional]
[More Information Needed]
Model Card Authors [optional]
[More Information Needed]
Model Card Contact
[More Information Needed]
- Downloads last month
- 112