Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Fetches trending models from Hugging Face with filtering by AI task, ML library, and sort metric (trending, likes, downloads). Outputs structured model data including likes, downloads, task type, and framework. Results can be exported to JSON for further processing.
Combines task, library, and popularity filtering in a single CLI call, replacing manual browsing across Hugging Face's website.
When to use it
- Checking which text-generation models are trending today
- Comparing PyTorch vs TensorFlow model popularity by downloads
- Finding top image-classification models sorted by likes
- Exporting a filtered model list to JSON for offline analysis
- Scheduling daily monitoring of new Hugging Face model releases
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Show me the top 5 trending text-generation models sorted by likes
- 1Runs hf_trends.py with -n 5 -t text-generation -s likes and the configured proxy flag
- 2Sends request to Hugging Face API through the proxy
- 3Retrieves model metadata including likes, downloads, task, and library fields
- 4Formats results into a ranked list with model IDs and metrics
Ranked list of 5 text-generation models showing model ID, like count, download count, and ML framework
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.