ChainFury
autolabel
| ChainFury | autolabel | |
|---|---|---|
| 3 | 10 | |
| 404 | 1,868 | |
| 4.2% | 6.6% | |
| 8.6 | 9.4 | |
| about 2 months ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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ChainFury
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🦋 ChainFury: open-source tool to create an LLM chatbot in 4 clicks!
Check out our repo at https://github.com/NimbleBoxAI/ChainFury and give us a star ⭐️ to show your support! Thanks!
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Create complex chat applications in just 4 clicks with LLMs
Our team accomplished this in a short period, and we'd love for you to check out our ChainFury Repo at https://github.com/NimbleBoxAI/ChainFury for more info and show your support by giving us a star ⭐️ on GitHub.
I wanted to share our latest project, ChainFury , with you all. It's an open-source tool that lets you build chat applications using LLMs with just 4 clicks
autolabel
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NLP Research in the Era of LLMs
Try this: https://github.com/refuel-ai/autolabel
Then the main challenge just becomes prompt design, which can sometimes be nebulous for NLP annotation.
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[P] Autolabel: data labeling with LLMs
Wanted to share an open source project we've been working on for the last few weeks: Autolabel is an open source Python library to label and enrich text datasets with LLMs (Large Language Models).
- Label clean and enrich text datasets with LLMs
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Show HN: Autolabel, a Python library to label and enrich text data with LLMs
Yep! I totally understand the concerns around not being able to share data externally - the library currently supports open source, self-hosted LLMs through huggingface pipelines (https://github.com/refuel-ai/autolabel/blob/main/src/autolab...), and we plan to add more support here for models like llama cpp that can be run without many constrains on hardware
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21-Jun-2023
Label, clean and enrich text datasets with Large Language Models (https://github.com/refuel-ai/autolabel)
- Show HN: Autolabel a Python library to label and enrich text data with LLMs
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LLMs can label data as well as human annotators, but 20 times faster
>> don't trust that there was no funny business going on in generating the results for this blog
All the datasets and labeling configs used for these experiments are available in our Github repo (https://github.com/refuel-ai/autolabel) as mentioned in the report. Hope these are useful!
What are some alternatives?
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GeniA - Your Engineering Gen AI Team member 🧬🤖💻
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