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Finetuner Alternatives
Similar projects and alternatives to finetuner
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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]
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Mergify
Updating dependencies is time-consuming.. Solutions like Dependabot or Renovate update but don't merge dependencies. You need to do it manually while it could be fully automated! Add a Merge Queue to your workflow and stop caring about PR management & merging. Try Mergify for free.
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Jina AI examples
Jina examples and demos to help you get started (by jina-ai)
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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.
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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
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DearPyGui
Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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pysot
SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
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CLIP
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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similarity
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
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Milvus
A cloud-native vector database, storage for next generation AI applications
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gradio
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
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sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
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wandb
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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pytorch-metric-learning
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
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txtai
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
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django-ninja
💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
finetuner reviews and mentions
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How can I create a dataset to refine Whisper AI from old videos with subtitles?
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.
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A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications
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.
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[D] Looking for an open source Downloadable model to run on my local device.
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.
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Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models
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.
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Classification using prompt or fine tuning?
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.
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Asking questions about lengthy texts
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.
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What are the best Python libraries to learn for beginners?
Actually further in applying ML, Finetuner is pretty handy for getting the last mile done which I found useful.
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Fine-tuning open source models to emulate ChatGPT for code explanation.
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.
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Efficient way to tune a network by changing hyperparameters?
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.
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Seeking advice on improving NLP search results
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.
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A note from our sponsor - Sonar
www.sonarsource.com | 28 Sep 2023
Stats
jina-ai/finetuner is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of finetuner is Python.