text-generation-webui-colab
ragas
| text-generation-webui-colab | ragas | |
|---|---|---|
| 4 | 10 | |
| 2,042 | 4,874 | |
| - | 17.7% | |
| 8.7 | 9.6 | |
| 5 months ago | 7 days ago | |
| Jupyter Notebook | Python | |
| The Unlicense | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
text-generation-webui-colab
- Text-Generation-Webui-Colab
-
what uncensored roleplay chatbot does to a mf
here
-
EdgeGPT on colab
Hello people, I just wanted to say that if you wanted to use EdgeGPT but couldn't, now you can using my colab (it works without cookies). I merged camenderu's and this colab, and added some tweaks too; it has an easy way to download extensions and all models that don't require to change webui files.
- What am i doing wrong? OPT-2.7b
ragas
-
Show HN: Ragas โ 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
-
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 โ Framework for RAG Evaluation
- Ragas: Open-source Evaluation framework for RAG pipelines
-
Building a customer support chatbot using GPT-3.5 and lLamaIndex๐
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 ๐
-
Patterns for Building LLM-Based Systems and Products
We have build RAGAS framework for this https://github.com/explodinggradients/ragas
-
[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?
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
deepeval - The LLM Evaluation Framework
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.
chameleon-llm - Codes for "Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models".
gpt-j-fine-tuning-example - Fine-tuning 6-Billion GPT-J (& other models) with LoRA and 8-bit compression
KoAlpaca - KoAlpaca: ํ๊ตญ์ด ๋ช ๋ น์ด๋ฅผ ์ดํดํ๋ ์คํ์์ค ์ธ์ด๋ชจ๋ธ
FastLoRAChat - Instruct-tune LLaMA on consumer hardware with shareGPT data
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
agenta - The all-in-one LLM developer platform: prompt management, evaluation, human feedback, and deployment all in one place.
comfyui-colab - comfyui colabs templates new nodes
ReAct - [ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models