Anthropic's Haiku Beats GPT-4 Turbo in Tool Use

• ollama

  196 62,615 9.9 Go

  Get up and running with Llama 3, Mistral, Gemma, and other large language models.

  

Not sure when they implemented this, but ollama now has a JSON mode [0]. Not function calling, but one of the simpler ways to get JSON in a local LLM. I'm using it with `knoopx/hermes-2-pro-mistral:7b-q8_0` and it's worked well for me so far.

0 - https://github.com/ollama/ollama/blob/main/docs/api.md#json-...

• outlines

  31 5,649 9.7 Python

  Structured Text Generation

  

No benchmarks, just my anecdotal experience trying to get local LLM's to respond with JSON. The method above works for my use case nearly 100% of the time. Other things I've tried (e.g. `outlines`[0]) are really slow or don't work at all. Would love to hear what others have tried!

0 - https://github.com/outlines-dev/outlines

• 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.

  

• instructor

  14 4,980 9.8 Python

  structured outputs for llms

Ah yes. Have you tried out instructor [0] or Guidance [1]?

[0]: https://github.com/jxnl/instructor/

• guidance

  23 17,357 9.8 Jupyter Notebook

  A guidance language for controlling large language models.

  

[1]: https://github.com/guidance-ai/guidance/tree/main

• tool-use-benchmark

  1 4 5.9 Jupyter Notebook
  

No fine tuning. Looks like he's do raw model capabilities with simple prompt. repo: https://github.com/parea-ai/tool-use-benchmark

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

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