The :8b and :latest tags actually point to :8b-instruct-q4_0 so I think we’re already good. You can check the tags page on ollama library and see the hashes for each tag to see which ones match.

Always pick the instruct version if you aren’t an expert.

I am a total noob in LLM, so I picked the largest model of 8B instructs.

Sure, here are the details I have so far:

1. You are interested in improving your workflow in data science and Python.
2. You work with databases from different sources like CSVs, accdb, and SQL, and want to create a module to extract and transform these databases into pandas DataFrames. You frequently use CSVs in different projects and need to prepare them every time by copying and pasting code. You want to create a module to import the databases and configurations, including columns, names, dates, and dtypes, to streamline the ETL process.
3. You are using rpy2 to interface between R and Python.
4. You often need to analyze different combinations of columns in a DataFrame, ensuring some columns are always analyzed together.

Let me know if there’s anything you’d like to modify or add!

1 and 3 are pretty good as baseline for my needs, but 2 and 4 were just specific problems I had to solve that are not something I need generally.

I know 8b models are okayish for fucking. I wouldn’t go with censored Meta models for that though.