| --- |
| 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. |
|
|
| ```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!") |
| |
