DearPy3D
finetuner
DearPy3D | finetuner | |
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4 | 36 | |
82 | 1,466 | |
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6.7 | 5.5 | |
over 2 years ago | 8 months ago | |
C++ | Python | |
MIT License | Apache License 2.0 |
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DearPy3D
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How does one make their own GUI from scratch? (no GUI libraries)
Dear PyGui is awesome and supports creating node editors. 3D is not really supported yet (although matrix functions are), but future versions will support 3D. The core developers are very much interested in 3D rendering. As a little test, Hoffstadt created DearPy3D. He is currently working on Pilotlight, which is still early stages and eventually will be the core of Dear PyGui version 3.
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The hand-picked selection of the best Python libraries released in 2021
Just a quick update since then is that Dear PyGui has reached version 1.0 and the API is now stable with a proper deprecation policy. Additional features include support for extremely dynamic tables, became faster still, introduction of the first steps into 3D and drawing transformations, support for multiple fonts, node editor and many small improvements and bug fixes. There are still many ideas for future development, including more 3D.
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Best gui framework for fast 2d operations and 3d render?
With regard to 3D, are you aware of DearPy3D by the same developers (still under development, also available under the MIT license)?
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Dear PyGui 3D Engine (Marvel)
hoffstadt/Marvel: Dear PyGui 3D Engine (early development) (github.com)
finetuner
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How do you think search will change with technology like ChatGPT, Bing’s new AI search engine and the upcoming Google Bard?
And all of that has something to do with finetuners. It basically fine-tunes AI models for specific use cases. With it can create a custom search experience that is tailored to their specific needs. I also wonder how this is going to be integrated into SEO tools soon since those tools are catered to traditional search engines.
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Combining multiple lists into one, meaningfully
Combining multiple lists into one is tough, but it's doable if you have the right approach. Fine-tuning GPT-3 might help, but finding enough examples is tough. You could use existing text data or manually label a set of training examples. A finetuner could be help too. It's a platform-agnostic toolkit that can fine-tune pre-trained models and it's customizable to do lots of tasks.
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speech_recognition not able to convert the full live audio to text. Please help me to fine-tune it.
You can adjust the pause threshold a little longer for pauses between and phrases. You can also use the phrase detection mode, which sets a time limit for the entire phrase instead of ending the transcription prematurely. If your microphone sensitivity is low, you can also try adjusting the energy threshold. If you want, you can use finetuners.
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Questions about fine-tuned results. Should the completion results be identical to fine-tune examples?
It's possible that completion results may be identical to fine-tuned examples, but not guaranteed. Even with the same prompt, slight variations in output are expected due to the nature of probabilistic language models. You can experiment with different settings and parameters, including those with finetuners like these.
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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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Is there a way I can feed the gpt3 model database object like tables? I know we can create fine tune model but not sure about the completion part. Please help!
I think you can convert your data into text and fine-tune the model on it. But that might not be the ideal way to go since you kind of base that on the model. Try transfer learning or finetuning with a 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.
What are some alternatives?
skweak - skweak: A software toolkit for weak supervision applied to NLP tasks
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]
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
Jina AI examples - Jina examples and demos to help you get started
magnum - Lightweight and modular C++11 graphics middleware for games and data visualization
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.
evidently - Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
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
awkward - Manipulate JSON-like data with NumPy-like idioms.
serve - ☁️ Build multimodal AI applications with cloud-native stack
processing - Source code for the Processing Core and Development Environment (PDE)
pysot - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.