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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
How can I create a dataset to refine Whisper AI from old videos with subtitles?
4 projects | /r/OpenAI | 17 Feb 2023
You can try creating your own dataset. Get some audio data that you want, preprocess it, and then create a custom dataset you can use to fine tune. You could use finetuners like these if you want as well.
A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications
6 projects | dev.to | 16 Feb 2023
We derived the dataset by pre-processing the deepfashion dataset using Finetuner. The image label generated by Finetuner is extracted and formatted to produce the text attribute of each product.
[D] Looking for an open source Downloadable model to run on my local device.
2 projects | /r/MachineLearning | 12 Feb 2023
You can either use Hugging Face Transformers as they have a lot of pre-trained models that you can customize. Or Finetuners like this one: which is a toolkit for fine-tuning multiple models.
Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models
2 projects | dev.to | 10 Feb 2023
Very recently, a few non-English and multilingual CLIP models have appeared, using various sources of training data. In this article, we’ll evaluate a multilingual CLIP model’s performance in a language other than English, and show how you can improve it even further using Jina AI’s Finetuner.
Classification using prompt or fine tuning?
2 projects | /r/GPT3 | 6 Feb 2023
you can try prompt-based classification or fine-tuning with a Finetuner. Prompts work well for simple tasks but fine-tuning may give better results for complex ones. Althouigh it's going to need more resources, but try both and see what works best for you.
Asking questions about lengthy texts
2 projects | /r/GPT3 | 4 Feb 2023
If you've got a set of Q&A pairs for your 60-page lease or medical paper, you could use finetuners to help answer questions about the text. But if you don't have those pairs, fine-tuning might not be good. Try summarizing the doc or extract the info. And if you're hitting the token limit, try using a bigger model or breaking up the text into smaller pieces.
What are the best Python libraries to learn for beginners?
7 projects | /r/learnpython | 30 Jan 2023
Actually further in applying ML, Finetuner is pretty handy for getting the last mile done which I found useful.
Fine-tuning open source models to emulate ChatGPT for code explanation.
2 projects | /r/learnmachinelearning | 27 Jan 2023
One option I’m considering is using fine tuners like the one from HuggingFace or Jina AI to fine-tune open source models like GPT-J or OPT to improve specific use-cases like code explanation. With the funding that we have, I wouldn’t want to cheap out on fine-tuning and expect something good.
Efficient way to tune a network by changing hyperparameters?
2 projects | /r/deeplearning | 25 Jan 2023
Off the top of my head you can either use Grid Search to test hyperparam combinations, Random Search to randomize hyperparams and Neural search uses ML to optimize hyperparameter tuning. You can use finetuners for this as well.
Seeking advice on improving NLP search results
4 projects | /r/LanguageTechnology | 22 Jan 2023
Back then, I came across some info about a self-supervised sentence embedding system that surpasses Sentence Transformers NLI models, but forgot where it was. You could use Jina’s Finetuner. It lets you boost your pre-trained models' performance, making them ready for production without having to spend a lot of time labeling or buying expensive hardware.
New free tool that uses fine-tuned BERT model to surface answers from research papers
7 projects | /r/LanguageTechnology | 28 Oct 2022
Tensorflow Ranking and Tensorflow similarity (maybe relevant/irrelevant contrastive learning?) look like they could be useful.
Non-Machine Learning Image Matching with a Vector DB
4 projects | news.ycombinator.com | 23 Aug 2022
There is the metric learning problem to learn a hash for similarity https://github.com/tensorflow/similarity
That said, I don't see many good models available for download on tfhub or huggingface optimized for it, but you can always programmatically modify your images (if you truly mean identical to humans) - change white balance, crop, rotate, select adjacent frames from videos, etc. and optimize a network that is small enough for you to be satisfied and see if that works, as a possible alternative.
[P] TensorFlow Similarity now self-supervised training
2 projects | /r/MachineLearning | 10 Jan 2022
Very happy to announce that as part of the 0.15 release, TensorFlow Similarity now support self-supervised learning using STOA algorithms. To help you get started we included in the release a detailed getting started notebook that you can run in Colab. This notebook shows you how to use SimSiam self-supervised pre-training to almost double the accuracy compared to a model trained from scratch on CIFAR 10.
What are some alternatives?
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
Jina AI examples - Jina examples and demos to help you get started
RWKV-LM - RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
jina - ☁️ Build multimodal AI applications with cloud-native stack
Promptify - Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
pgANN - Fast Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database.
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
quaterion - Blazing fast framework for fine-tuning similarity learning models
ContraD - Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)
pysot - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time