causal-chains
Library for creating causal chains using language models. (by helliun)
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 (by promptslab)
Our great sponsors
| causal-chains | Promptify | |
|---|---|---|
| 1 | 29 | |
| 69 | 2,574 | |
| - | 11.6% | |
| 7.4 | 10.0 | |
| 8 months ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
causal-chains
Posts with mentions or reviews of causal-chains.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-12.
Promptify
Posts with mentions or reviews of Promptify.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-13.
-
A minimal design pattern for LLM-powered microservices with FastAPI & LangChain
You're absolutely correct, and I agree that there's potentially a risk of quality loss. But likewise, since these are all intrinsically linked, it may be possible to leverage strength by combining these tasks. I'm unaware of a paper reviewing the reliability and/or performance of LLMs in this specific scenario. If you find any, do share :) With regards to generating JSON responses - there are simple ways to nudge the model and even validate it, using libraries such as https://github.com/promptslab/Promptify, https://github.com/eyurtsev/kor and https://github.com/ShreyaR/guardrails
-
[P] Extracting Causal Chains from Text Using Language Models
Awesome project! I am working on something similar using Promptify (extending this PR -> https://github.com/promptslab/Promptify/issues/3)
- Classification using prompt or fine tuning?
What are some alternatives?
When comparing causal-chains and Promptify you can also consider the following projects:
finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.
kor - LLM(😽)