MARKET RESEARCH
Brief the ML team when a watched HuggingFace model crosses a download threshold
Polls HuggingFace daily for models matching your tracked tags and tasks, and when one crosses a download-count threshold it posts an LLM-written one-paragraph brief to Slack.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule
- ActionQuery HuggingFace models by tracked tags and tasksHugging Face
- LogicKeep only models over the download threshold and not yet briefed
- ActionSummarize each model card into a short briefOpenAI
- OutputPost brief with download count and link to SlackSlack
What it does
Watches HuggingFace for models that match your team's areas of interest (tags, pipeline tasks, library) and surfaces only the ones gaining real traction. When a matching model's cumulative downloads cross a threshold you set, it drafts a short, plain-English brief and drops it in your ML channel so the team learns about momentum models without scrolling the Hub.
When to use it
Use it when your ML team needs to stay current on fast-rising open models in specific domains (e.g. speech, embeddings, vision-language) but doesn't want a firehose of every new upload. The download threshold filters hype from adoption.
How it works
- 1A daily schedule fires the run.
- 2HuggingFace is queried for models filtered by your tracked tags and tasks, sorted by recent download velocity.
- 3A filter keeps only models whose downloads exceed the configured threshold and that haven't been briefed before.
- 4OpenAI summarizes each qualifying model's card into a two-sentence brief covering what it does and why it matters.
- 5The brief, with download count and Hub link, is posted to the Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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