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marlonbino/
ner-distilbert

Name: ner-distilbert
Availability: InStock

pytorch

ner

mlflow

ner_training_synthetic_v1.jsonl

apache-2.0

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ner_distillbert

Model Description

This is a Named Entity Recognition (NER) model fine-tuned on DistilBERT-base-cased for extracting entities from English text. The model is trained on synthetic data (ner_dataset_2.jsonl) and is optimized for token classification tasks where each word/token in the input text is classified into predefined entity categori.

Model Details:

Model Name: ner_distillbert
Version: 1
Task: Ner
Framework: pytorch
Language(s): en
License: apache-2.0

Intended Uses

This model is designed for ner tasks. Please evaluate on your specific use case before production deployment.

Training Details

Training Data

Dataset: ner_training_synthetic_v1.jsonl
Dataset Size: Not specified

Training Configuration

Usage

Installation

bash

pip install transformers torch  # For transformers models
# OR
pip install -r requirements.txt  # For other frameworks

Basic Usage

python

# Load and use the model
from inference import Model  # See inference.py in the repository

model = Model()
predictions = model.predict(["Your input data here"])
print(predictions)

MLflow Tracking

Experiment: N/A
Run ID: N/A
Training Date: N/A

Citation

bibtex

@misc{ner_distillbert_1,
  title={ner_distillbert},
  author={BITZ-AI TEAM},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/marlonbino/ner_distillbert}
}

marlonbino/ner-distilbert