请参见原始 SKILL.md 文档（已保留原始代码块、命令行指令和 Markdown 格式，不再重复翻译)
Quick Start
Fetch the top trending models:
scripts/hf_trends.py -n 10 -p http://172.28.96.1:10808
Core 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://172.28.96.1:10808
Filter 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://172.28.96.1:10808
Common 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://172.28.96.1:10808
Export 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://172.28.96.1:10808
Proxy Configuration
The script requires an HTTP proxy to access Hugging Face API (network restrictions).
Use the -p flag:
scripts/hf_trends.py -p http://172.28.96.1:10808
For 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)
============================================================
⭐ 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>&1
Task-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://172.28.96.1:10808
Framework-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://172.28.96.1:10808
Integration with OpenClaw
Use within OpenClaw sessions:
# Fetch trending models programmatically
from skills.huggingface-trends.scripts import hf_trendsfetcher = 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://172.28.96.1:10808
Check 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://172.28.96.1:10808
Dependencies Missing
Problem: "requests package not installed"
Solution: Install required dependencies:
pip install requests
Technical 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.
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