A collection of transformer models built using huggingface for various tasks.
Project description
transformers-collection
- A collection of transformer models built using huggingface for various tasks. Training done using pytorch lightning.
- Datasets, models and tokenizers from hugging face.
- Goal: Get familiar with huggingface and pytorch lightning ecosystems.
Get started
Train Models using the library
- To train models, install using pip:
pip install transformers_collection
- check installation:
transformers-collection version
Clone project and modify code
To play around with the code clone the repo:
git clone git@github.com:aadhithya/transformers-collection.git
- Install poetry:
pip install poetry
- Intsall dependencies:
poetry install
Note: poetry install
will create a new venv.
Note: poetry/pip install
installs CPU version of pytorch if not available, please make sure to install CUDA version if needed.
Train a model
-
Create the yaml config file for the model (see configs/sentiment-clf.yml for example).
-
train model using:
transformers-collection train /path/to/config.yml
-
For a list of supported models, see section Supported Models.
Supported Models / Task
The following models are planned:
Model | Dataset | Status | Checkpoint |
---|---|---|---|
Sentiment/Emotion Classification | emotion | ✅ | TBD |
Text Summarization | 🗓️ Planned | TBD |
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