kiri
BERTweet
| kiri | BERTweet | |
|---|---|---|
| 12 | 1 | |
| 240 | 557 | |
| 0.0% | 0.4% | |
| 3.2 | 2.6 | |
| almost 3 years ago | 5 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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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.
BERTweet
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A pre-trained BERT-like model with recent events?
Not sure if that's what you are looking for, but BERTweet has model trained on tweets containing COVID keywords https://github.com/VinAIResearch/BERTweet
What are some alternatives?
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
simpletransformers - Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
DeBERTa - The implementation of DeBERTa
qagnn - [NAACL 2021] QAGNN: Question Answering using Language Models and Knowledge Graphs 🤖
CoWin-Vaccine-Notifier - Automated Python Script to retrieve vaccine slots availability and get notified when a slot is available.
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
nlu - 1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
Questgen.ai - Question generation using state-of-the-art Natural Language Processing algorithms
covid-19-germany-gae - COVID-19 statistics for Germany. For states and counties. With time series data. Daily updates. Official RKI numbers.
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.
FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.