Install
openclaw skills install huggingface-trendsMonitor and fetch trending models from Hugging Face with support for filtering by task, library, and popularity metrics. Use when users want to check trending AI models, compare model popularity, or explore popular models by task or library. Supports export to JSON and formatted output.
openclaw skills install huggingface-trendsFetch the top trending models:
scripts/hf_trends.py -n 10 -p http://172.28.96.1:10808
Basic usage:
# Get top 10 trending models
scripts/hf_trends.py -n 10 -p http://172.28.96.1:10808
# Get top 5 most liked models
scripts/hf_trends.py -n 5 -s likes -p http://172.28.96.1:10808
# Get most downloaded models
scripts/hf_trends.py -n 10 -s downloads -p http://172.28.96.1:10808
Filter models by specific AI tasks:
# Text generation models
scripts/hf_trends.py -n 10 -t text-generation -p http://172.28.96.1:10808
# Image classification models
scripts/hf_trends.py -n 10 -t image-classification -p http://172.28.96.1:10808
# Translation models
scripts/hf_trends.py -n 10 -t translation -p http://172.28.96.1:10808
Common task filters:
text-generation - Large language modelsimage-classification - Vision modelsimage-to-text - Multimodal modelstranslation - Machine translationsummarization - Text summarizationquestion-answering - QA modelsFilter by ML framework:
# PyTorch models only
scripts/hf_trends.py -n 10 -l pytorch -p http://172.28.96.1:10808
# TensorFlow models only
scripts/hf_trends.py -n 10 -l tensorflow -p http://172.28.96.1:10808
# JAX models
scripts/hf_trends.py -n 10 -l jax -p http://172.28.96.1:10808
Save results for further analysis:
# Export to JSON file
scripts/hf_trends.py -n 10 -j trending_models.json -p http://172.28.96.1:10808
# Export with specific filters
scripts/hf_trends.py -n 20 -t text-generation -j text_models.json -p http://172.28.96.1:10808
The script requires an HTTP proxy to access Hugging Face API (network restrictions).
Use the -p flag:
scripts/hf_trends.py -p http://172.28.96.1:10808
For most WSL2 environments with v2rayN:
http://172.28.96.1:10808http://$(ip route show | grep default | awk '{print $3}'):10808| Flag | Long Form | Description | Default |
|---|---|---|---|
-n | --limit | Number of models to fetch | 10 |
-s | --sort | Sort by: trending, likes, downloads, created | trending |
-t | --task | Filter by task/pipeline | None |
-l | --library | Filter by library (pytorch, tensorflow, jax) | None |
-j | --json | Export results to JSON file | None |
-p | --proxy | Proxy URL for HTTP requests | None |
The script displays models in a structured format:
🤖 Hugging Face 热门模型 (5 个)
============================================================
1. moonshotai/Kimi-K2.5
⭐ 2.0K likes 📥 647.6K downloads
📊 Task: image-text-to-text 📚 Library: transformers
📅 Created: 2026-01-01 Updated: N/A
...
Each model entry includes:
Check trending models daily for new releases:
# Create cron job for daily monitoring
0 9 * * * cd /home/ltx/.openclaw/workspace && \
/home/ltx/.openclaw/workspace/skills/huggingface-trends/scripts/hf_trends.py \
-n 20 -p http://172.28.96.1:10808 >> /tmp/hf-trends.log 2>&1
Explore popular models for specific AI tasks:
# Research trending text generation models
scripts/hf_trends.py -n 15 -t text-generation -s likes -p http://172.28.96.1:10808
# Find popular image-to-text models
scripts/hf_trends.py -n 15 -t image-to-text -s downloads -p http://172.28.96.1:10808
Compare models by ML framework:
# Compare PyTorch vs TensorFlow popularity
scripts/hf_trends.py -n 20 -l pytorch -j pytorch_models.json -p http://172.28.96.1:10808
scripts/hf_trends.py -n 20 -l tensorflow -j tensorflow_models.json -p http://172.28.96.1:10808
Use within OpenClaw sessions:
# Fetch trending models programmatically
from skills.huggingface-trends.scripts import hf_trends
fetcher = hf_trends.HuggingFaceTrends(proxy="http://172.28.96.1:10808")
models = fetcher.fetch_trending_models(limit=10)
# Format for display
output = fetcher.format_models(models)
print(output)
Problem: "Network is unreachable" or connection errors
Solution: Ensure proxy is specified with -p flag:
scripts/hf_trends.py -p http://172.28.96.1:10808
Check if v2rayN proxy is running on Windows.
Problem: "No models found"
Solution: Try different filters or increase limit:
scripts/hf_trends.py -n 50 -p http://172.28.96.1:10808
Problem: "requests package not installed"
Solution: Install required dependencies:
pip install requests
See Hugging Face API Documentation for more details on model metadata and available filters.