Show HN: Autolabel, a Python library to label and enrich text data with LLMs

• autolabel

  10 1,841 9.4 Python

  Label, clean and enrich text datasets 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

• llama.cpp

  778 57,984 10.0 C++

  LLM inference in C/C++

You can self-host an open-source model. Llama CCP is a very popular project with great docs.

https://github.com/ggerganov/llama.cpp

You need to be careful about liscencing - some of these models its a legal grey area if you can use them for commercial projects.

A popular compression methodology at the moment is 'quantization', using lower precision model weights for inference to reduce memory requirements. I find it a bit hard to evaluate which open source models are best, and how they are impacted by quantisation.

You can also use the Open-AI API. They don't use the data, or store beyond 30 days, which they use for fraud-monitoring. It doesn't seem hugely different to using something like Slack/Google doc/AWS.

https://openai.com/policies/api-data-usage-policies

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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