GLM-4.7-REAP-45

235
2
license:apache-2.0
by
0xSero
Language Model
OTHER
New
235 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Training Data Analysis

šŸ”µ Good (6.0/10)

Researched training datasets used by GLM-4.7-REAP-45 with quality assessment

Specialized For

general
multilingual

Training Datasets (1)

c4
šŸ”µ 6/10
general
multilingual
Key Strengths
  • ā€¢Scale and Accessibility: 750GB of publicly available, filtered text
  • ā€¢Systematic Filtering: Documented heuristics enable reproducibility
  • ā€¢Language Diversity: Despite English-only, captures diverse writing styles
Considerations
  • ā€¢English-Only: Limits multilingual applications
  • ā€¢Filtering Limitations: Offensive content and low-quality text remain despite filtering

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

Observation Reuse (Instant Multi-Ratio Pruning)bash
# First run: compute observations (~5 hours)
python prune.py --compression-ratio 0.40 --output_file_name observations.pt

# Subsequent runs: instant pruning (<5 minutes)
python prune.py --compression-ratio 0.30 --load_observations observations.pt
python prune.py --compression-ratio 0.50 --load_observations observations.pt

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