Neurotech-HQ/swahili-ner-spacy

Swahili NER model trained using spacy # 🪐 spaCy Project: Demo NER in a new pipeline (Named Entity Recognition) A minimal demo NER project for spaCy v3 adapted from the spaCy v2 `train_ner.py` example script for creating an NER component in a new pipeline. ## 📋 project.yml The `project.yml` defines the data assets required by the project, as well as the available commands and workflows. For details, see the spaCy projects documentation. ### ⏯ Commands The following commands are defined by the project. They can be executed using [`spacy project run [name]`](spacy.io). Commands are only re-run if their inputs have changed. | Command | Description | | --- | --- | | `download` | Download a spaCy model with pretrained vectors | | `convert` | Convert the data to spaCy's binary format | | `create-config` | Create a new config with an NER pipeline component | | `train` | Train the NER model | | `train-with-vectors` | Train the NER model with vectors | | `evaluate` | Evaluate the model and export metrics | | `package` | Package the trained model as a pip package | | `visualize-model` | Visualize the model's output interactively using Streamlit | ### ⏭ Workflows The following workflows are defined by the project. They can be executed using [`spacy project run [name]`](spacy.io) and will run the specified commands in order. Commands are only re-run if their inputs have changed. | Workflow | Steps | | --- | --- | | `all` | `convert` → `create-config` → `train` → `evaluate` | ### 🗂 Assets The following assets are defined by the project. They can be fetched by running `spacy project assets` in the project directory. | File | Source | Description | | --- | --- | --- | | `assets/train.json` | Local | Demo training data converted from the v2 `train_ner.py` example with `srsly.write_json("train.json", TRAIN_DATA)` | | `assets/dev.json` | Local | Demo development data |