TEXTOIR
happy-transformer
| TEXTOIR | happy-transformer | |
|---|---|---|
| 1 | 1 | |
| 179 | 500 | |
| 4.5% | - | |
| 7.7 | 9.0 | |
| 3 months ago | about 2 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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TEXTOIR
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[D] Extracting next action from conversation
- Intent extraction models such as https://github.com/thuiar/textoir. My problem with this approach is that they are multi-label classifiers and usually focused on single-sentence classification "Can you get me a table?" would be assigned to the "Reservation" label. I feel that I would lose information such as "Meet at 10PM in this address."
happy-transformer
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GPT-Neo-125M-AID (Mia) oversight + retrained
This appears to be an actual issue with Happy Transformer judging by a GitHub issue I've found of the same problem.
What are some alternatives?
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
FinBERT-QA - Financial Domain Question Answering with pre-trained BERT Language Model
small-text - Active Learning for Text Classification in Python
gector - Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)
quickai - QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
FreeDiscovery - Web Service for E-Discovery Analytics
bllip-parser - BLLIP reranking parser (also known as Charniak-Johnson parser, Charniak parser, Brown reranking parser) See http://pypi.python.org/pypi/bllipparser/ for Python module.
tableQA - AI Tool for querying natural language on tabular data.