metadata
language:
- en
tags:
- intent-recognition
- text-classification
- crop-recommendation
- price-prediction
metrics:
- accuracy
pipeline_tag: text-classification
Intent Recognition Model
This model is designed for intent recognition in crop recommendation and price prediction.
It uses Natural Language Processing (NLP) techniques to classify user input into different intents.
📌 Usage
To use this model, download the .pkl files and load them using Python.
from huggingface_hub import hf_hub_download
import pickle
# Load the model and vectorizer
model_path = hf_hub_download(repo_id="<your-username>/<your-model-name>", filename="intent_model.pkl")
vectorizer_path = hf_hub_download(repo_id="<your-username>/<your-model-name>", filename="vectorizer_intent.pkl")
with open(model_path, "rb") as f:
model = pickle.load(f)
with open(vectorizer_path, "rb") as f:
vectorizer = pickle.load(f)
print("Model and vectorizer successfully loaded!")