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 |
Metadata
Release files for transformers-collection 0.2.0
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| transformers_collection-0.2.0-py3-none-any.whl | Python 3 | none | any | Details for transformers_collection-0.2.0-py3-none-any.whl |
Total release size: 12.0 kB
Release files / transformers_collection-0.2.0.tar.gz
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Release files / transformers_collection-0.2.0-py3-none-any.whl
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