FinBERT-QA
kiri
| FinBERT-QA | kiri | |
|---|---|---|
| 1 | 12 | |
| 113 | 240 | |
| - | 0.0% | |
| 0.0 | 3.2 | |
| 11 months ago | about 3 years ago | |
| Python | Python | |
| - | GNU General Public License v3.0 or later |
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FinBERT-QA
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Best way to approach financial statement analysis with NLP and Image Recognition?
Open Domain Question Answering (ODQA) using a deep transformer NLP model that has been fine tune trained on a financial domain dataset such as FiQA.
kiri
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[P][D] NLP question - Question Answering AI
I'm one of the authors of Backprop, a library built for transfer learning.
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Backprop: Use and finetune models in a single line of code
I'd like to share Backprop, an open source library I've been co-authoring for the last few months.
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[P] Backprop Model Hub: a curated list of state-of-the-art models
We've also got an open-source library that makes using + finetuning these models possible in a few lines of code.
- Show HN: Backprop – a simple library to use and finetune state-of-the-art models
- Show HN: Backprop – a library to easily finetune and use state-of-the-art models
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[P] Backprop: a library to easily finetune and use state-of-the-art models
I'd like to share Backprop, a Python library I've been co-authoring for the last few months. Our goal is to make finetuning and using models as easy as possible, even without extensive ML experience.
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GPT Neo: open-source GPT-3-like model with pretrained weights available
You might get some really promising results with finetuning.
If anything, you could build writing assistance that almost automates responses.
I've been co-authoring a library that lets you finetune such models in a single line of code.
https://github.com/backprop-ai/backprop
In specific the text generation finetuning example should be what you are looking for: https://github.com/backprop-ai/backprop/blob/main/examples/F...
Hope this helps, happy to chat more about it. Pretty curious about the results.
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NLP Model for extracting specific text from raw text
Here's an example Jupyter Notebook for finetuning T5. Full disclosure, I work on this library myself -- but it could be helpful.
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[D] Need help with document classifier and later prediction of text
I'm working on a library that hopefully makes working with some of these a bit easier -- here's an example notebook for running text classification with the BART checkpoint, if you're interested. If you need more task-specific finetuning for text classification, that's going to be rolled out in the near future.
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Generating notes from text
I'm working on a library that includes a few different ML tasks, including summarisation. It uses a pretrained version of Google's T5 transformer model, which we host on Hugging Face with some details on how it was trained.
What are some alternatives?
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
BERT-QE - Code and resources for the paper "BERT-QE: Contextualized Query Expansion for Document Re-ranking".
simpletransformers - Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
qagnn - [NAACL 2021] QAGNN: Question Answering using Language Models and Knowledge Graphs 🤖
KitanaQA - KitanaQA: Adversarial training and data augmentation for neural question-answering models
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
kiri - Kiri is a visual tool designed for reviewing schematics and layouts of KiCad projects that are version-controlled with Git.
Questgen.ai - Question generation using state-of-the-art Natural Language Processing algorithms
TextFooler - A Model for Natural Language Attack on Text Classification and Inference