kiri
jiant
kiri | jiant | |
---|---|---|
12 | 2 | |
240 | 1,604 | |
0.0% | 0.2% | |
3.2 | 0.0 | |
almost 3 years ago | 10 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 β a simple library to use and finetune state-of-the-art models
- Show HN: Backprop β 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.
jiant
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Any recommendation for the replacement of the toolkit jiant? [Research] [Discussion]
I am doing research in NLP with the toolkit jiant (https://github.com/nyu-mll/jiant). It is a quite nice and easy-to-use tool. Unfortunately, it stopped being maintained. I wonder is there any other recommendation that I can use to replace it?
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Looking for a code base to implement multi-task learning in NLP
Jiant should fulfill 1, 2, 4 and 5.
What are some alternatives?
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
SGDepth - [ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
simpletransformers - Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
allennlp - An open-source NLP research library, built on PyTorch.
qagnn - [NAACL 2021] QAGNN: Question Answering using Language Models and Knowledge Graphs π€
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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.
Questgen.ai - Question generation using state-of-the-art Natural Language Processing algorithms
PaddleNLP - π Easy-to-use and powerful NLP and LLM library with π€ Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including πText Classification, π Neural Search, β Question Answering, βΉοΈ Information Extraction, π Document Intelligence, π Sentiment Analysis etc.
YOLOP - You Only Look Once for Panopitic Driving Perception.οΌMIR2022οΌ