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Huggingface Trends

从Hugging Face获取热门AI模型,支持按任务、库和热度筛选。可用于查看趋势模型、比较热度或探索流行模型。支持JSON导出和格式化输出。

person作者: tianxingleohubclawhub

Hugging Face Trending Models

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 models
  • image-classification - Vision models
  • image-to-text - Multimodal models
  • translation - Machine translation
  • summarization - Text summarization
  • question-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)
============================================================
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>&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_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://172.28.96.1:10808

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.