GitHub / mahikshith / Transformer-Text-Summarizer-Fine-tuning-with-ETL-pipeline-and-Deployment
Fine tuning pre-trained transformer model for custom text summarization with ETL pipeline and end to end deployment
Stars: 2
Forks: 0
Open issues: 0
License: gpl-3.0
Language: Jupyter Notebook
Size: 116 KB
Dependencies parsed at:
23
Created at: 5 months ago
Updated at: 4 months ago
Pushed at: 4 months ago
Last synced at: 9 days ago
Topics: ci-cd-pipeline, docker, etl-pipeline, fastapi, fine-tuning, huggingface-datasets, huggingface-transformers, nlp-machine-learning, nvidia-cuda, python, text-summarization, transfer-learning, transformer
Dockerfile
docker
requirements.txt
pypi
- Jinja2 ==3.1.2
- boto3 *
- datasets *
- ensure ==1.0.2
- fastapi ==0.78.0
- matplotlib *
- mypy-boto3-s3 *
- nltk *
- notebook *
- pandas *
- py7zr *
- python-box ==6.0.2
- pyyaml *
- rouge_score *
- sacrebleu *
- scikit-learn *
- torch *
- tqdm *
- transformers *
- uvicorn ==0.18.3
setup.py
pypi
.github/workflows/main.yaml
actions
- actions/checkout v3 composite
- aws-actions/amazon-ecr-login v1 composite
- aws-actions/configure-aws-credentials v1 composite