|
--- |
|
license: mit |
|
language: |
|
- en |
|
library_name: transformers |
|
pipeline_tag: tabular-classification |
|
inference: true |
|
--- |
|
# My Model |
|
|
|
This is a model for predicting issue resolution times based on various features. It uses an LSTM neural network for classification. |
|
|
|
## How to use |
|
|
|
```python |
|
import tensorflow as tf |
|
from keras.models import load_model |
|
|
|
# Load the model |
|
model = load_model("my_model.h5") |
|
|
|
# Prepare your input data (example) |
|
# X = ... |
|
|
|
# Predict |
|
predictions = model.predict(X) |
|
Model Details |
|
``` |
|
Framework: TensorFlow / Keras / Bert |
|
Input features: Text and numerical features |
|
Output: Duration category (short, medium, long) |
|
Performance |
|
|
|
Precision: 0.9969 |
|
Recall: 0.9985 |
|
F1 Score: 0.9977 |
|
""" |
