metadata
language:
- en
license: apache-2.0
tags:
- llm
- classification
- religion-prediction
datasets:
- custom
model-index:
- name: onomastics
results:
- task:
type: text-classification
name: Religion Classification
dataset:
name: custom-dataset
type: text
metrics:
- name: accuracy
type: accuracy
value: 0.92
🧾 Model Card: your-model-name
📌 Model Details
- Developed by: gpsworld8800
- Model type: Large Language Model
- Architecture: LLaMA
- Language(s): English / Hindi / Multilingual
- License: Apache 2.0
🛠️ Intended Uses
- Predicting religion/ethnicity from Indian names
- Research on Indian onomastics & linguistics
- Educational or demo purposes
⚠️ Not intended for:
- Making decisions in sensitive contexts (hiring, loans, etc.)
- Any discriminatory use
🧑💻 How to Use
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("gpsworld8800/onomastics")
model = AutoModelForCausalLM.from_pretrained("gpsworld8800/onomastics")
inputs = tokenizer("Prathamesh Gate", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))