openvino-ai-plugins-gimp
ragas
| openvino-ai-plugins-gimp | ragas | |
|---|---|---|
| 5 | 10 | |
| 380 | 4,874 | |
| 9.4% | 17.7% | |
| 8.8 | 9.6 | |
| 12 days ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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openvino-ai-plugins-gimp
- FLaNK Stack Weekly 19 Feb 2024
- FLaNK Stack 05 Feb 2024
- Intel slaps forehead, says I got it: AI PCs. Sell them AI PCs
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Has anyone tried training SD models on the A770?
Apparently, you still have to use OpenVino as a plugin in GIMP for access to Stable Diffusion with the ARC A770. https://github.com/intel/openvino-ai-plugins-gimp
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We really need an Automatic1111 Gimp extension
It seems that Intel already has something similar, a plugin for GIMP called openvino-ai-plugins-gimp. Stable diffusion included.
ragas
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Show HN: Ragas – the de facto open-source standard for evaluating RAG pipelines
congrats on launching! i think my continuing struggle with looking at Ragas as a company rather than an oss library is that the core of it is like 8 metrics (https://github.com/explodinggradients/ragas/tree/main/src/ra...) that are each 1-200 LOC. i can inline that easily in my app and retain full control, or model that in langchain or haystack or whatever.
why is Ragas a library and a company, rather than an overall "standard" or philosophy (eg like Heroku's 12 Factor Apps) that could maybe be more robust?
(just giving an opp to pitch some underappreciated benefits of using this library)
- FLaNK 04 March 2024
- FLaNK Stack 05 Feb 2024
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SuperDuperDB - how to use it to talk to your documents locally using llama 7B or Mistral 7B?
Also, at some point you'll need to get serious about evaluation (trust me, you will). You may be interested in https://github.com/explodinggradients/ragas
- Ragas – Framework for RAG Evaluation
- Ragas: Open-source Evaluation framework for RAG pipelines
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Building a customer support chatbot using GPT-3.5 and lLamaIndex🚀
The problem becomes worse if you want to inspect outputs from not just one, but several different queries. Luckily, there are several free open source packages such as ragas and DeepEval that can help evaluate your chatbot so you don't have to manually do it 😌
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Patterns for Building LLM-Based Systems and Products
We have build RAGAS framework for this https://github.com/explodinggradients/ragas
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[R] All about evaluating Large language models
Hi u/thecuteturtle, I am building open-source projects for evaluating LLM-based applications. Check it out https://github.com/explodinggradients/ragas and if you like to collaborate let me know :)
What are some alternatives?
stable-gimpfusion - A Gimp plugin that brings StableDiffusion functionality through Automatic1111's API
deepeval - The LLM Evaluation Framework
axodox-machinelearning - This repository contains a pure C++ ONNX implementation of multiple offline AI models, such as StableDiffusion (1.5 and XL), ControlNet, Midas, HED and OpenPose.
chameleon-llm - Codes for "Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models".
WhisperFusion - WhisperFusion builds upon the capabilities of WhisperLive and WhisperSpeech to provide a seamless conversations with an AI.
Local-LLM-Langchain - Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
jepa - PyTorch code and models for V-JEPA self-supervised learning from video.
FastLoRAChat - Instruct-tune LLaMA on consumer hardware with shareGPT data
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
agenta - The all-in-one LLM developer platform: prompt management, evaluation, human feedback, and deployment all in one place.
openvino - OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
text-generation-webui-colab - A colab gradio web UI for running Large Language Models