- name
- huggingface-trends
- description
- Monitor 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.
Hugging Face Trending Models
Quick Start
Fetch the top trending models:
scripts/hf_trends.py -n 10 -p http://172.28.96.1:10808Core Features
Fetch Trending Models
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://172.28.96.1:10808Filter by Task
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://172.28.96.1:10808Common task filters:
text-generation- Large language modelsimage-classification- Vision modelsimage-to-text- Multimodal modelstranslation- Machine translationsummarization- Text summarizationquestion-answering- QA models
Filter by Library
Filter 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://172.28.96.1:10808Export to JSON
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://172.28.96.1:10808Proxy Configuration
The script requires an HTTP proxy to access Hugging Face API (network restrictions).
Use the -p flag:
scripts/hf_trends.py -p http://172.28.96.1:10808For most WSL2 environments with v2rayN:
- Proxy URL:
http://172.28.96.1:10808 - Or use dynamic IP:
http://$(ip route show | grep default | awk '{print $3}'):10808
Command-Line Options
| 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 |
Output Format
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
...Model Information
Each model entry includes:
- Model ID: Full Hugging Face model name
- Likes: Number of likes (popularity metric)
- Downloads: Total download count
- Task: Primary task/pipeline (e.g., text-generation)
- Library: ML framework (transformers, pytorch, tensorflow)
- Created/Updated: Date information
Use Cases
Daily Monitoring
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>&1Task-Specific Research
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://172.28.96.1:10808Framework-Specific Analysis
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://172.28.96.1:10808Integration with OpenClaw
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)Troubleshooting
Network Errors
Problem: "Network is unreachable" or connection errors
Solution: Ensure proxy is specified with -p flag:
scripts/hf_trends.py -p http://172.28.96.1:10808Check if v2rayN proxy is running on Windows.
Empty Results
Problem: "No models found"
Solution: Try different filters or increase limit:
scripts/hf_trends.py -n 50 -p http://172.28.96.1:10808Dependencies Missing
Problem: "requests package not installed"
Solution: Install required dependencies:
pip install requestsTechnical Notes
- API Limitation: Hugging Face's public API doesn't provide a dedicated trending endpoint without authentication. The script fetches recent models and sorts by popularity metrics.
- Proxy Requirement: Due to network restrictions, all requests must go through a proxy. The script supports HTTP proxy configuration.
- Rate Limits: The public API has rate limits. Avoid making too many requests in quick succession.
- Data Freshness: Models are fetched from the Hugging Face API. Recent changes may take time to reflect.
Reference
See Hugging Face API Documentation for more details on model metadata and available filters.