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\n[![Downloads](https://pepy.tech/badge/happytransformer)](https://pepy.tech/project/happytransformer)\n[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://happytransformer.com)\n![PyPI](https://img.shields.io/pypi/v/happytransformer)\n[![](https://github.com/EricFillion/happy-transformer/workflows/build/badge.svg)](https://github.com/EricFillion/happy-transformer/actions)\n\n# Happy Transformer \n**Documentation and news: [happytransformer.com](http://happytransformer.com)**\n\n\n\nJoin our Discord server: [![Support Server](https://img.shields.io/discord/839263772312862740.svg?label=Discord\u0026logo=Discord\u0026colorB=7289da\u0026style=?style=flat-square\u0026logo=appveyor)](https://discord.gg/psVwe3wfTb)\n\n\n\n![HappyTransformer](logo.png)\n\nHappy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.\n\n## 3.0.0 \n1. DeepSpeed for training \n2. Apple's MPS for training and inference \n3. WandB to track training runs \n4. Data supplied for training is automatically split into portions for training and evaluating\n5. Push models directly to Hugging Face's Model Hub\n\nRead about the full 3.0.0 update including breaking changes [here](https://happytransformer.com/news/). \n\n\n## Tasks \n  \n| Tasks                    | Inference | Training   |\n|--------------------------|-----------|------------|\n| Text Generation          | ✔         | ✔          |\n| Text Classification      | ✔         | ✔          | \n| Word Prediction          | ✔         | ✔          |\n| Question Answering       | ✔         | ✔          | \n| Text-to-Text             | ✔         | ✔          | \n| Next Sentence Prediction | ✔         |            | \n| Token Classification     | ✔         |            | \n\n## Quick Start\n```sh\npip install happytransformer\n```\n\n```python\n\nfrom happytransformer import HappyWordPrediction\n#--------------------------------------#\nhappy_wp = HappyWordPrediction()  # default uses distilbert-base-uncased\nresult = happy_wp.predict_mask(\"I think therefore I [MASK]\")\nprint(result)  # [WordPredictionResult(token='am', score=0.10172799974679947)]\nprint(result[0].token)  # am\n```\n\n## Maintainers\n- [Eric Fillion](https://github.com/ericfillion)  Lead Maintainer\n- [Ted Brownlow](https://github.com/ted537) Maintainer\n\n\n## Tutorials \n[Text generation with training (GPT-Neo)](https://youtu.be/GzHJ3NUVtV4)\n\n[Text classification (training)](https://www.vennify.ai/train-text-classification-transformers/) \n\n[Text classification (hate speech detection)](https://youtu.be/jti2sPQYzeQ) \n\n[Text classification (sentiment analysis)](https://youtu.be/Ew72EAgM7FM)\n\n[Word prediction with training (DistilBERT, RoBERTa)](https://youtu.be/AWe0PHsPc_M)\n\n[Top T5 Models ](https://www.vennify.ai/top-t5-transformer-models/)\n\n[Grammar Correction](https://www.vennify.ai/grammar-correction-python/)\n\n[Fine-tune a Grammar Correction Model](https://www.vennify.ai/fine-tune-grammar-correction/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEricFillion%2Fhappy-transformer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FEricFillion%2Fhappy-transformer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEricFillion%2Fhappy-transformer/lists"}