ziadrone / tot_runs_strict_limit_models

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Introduction of tot_runs_strict_limit_models

Model Details of tot_runs_strict_limit_models

TOT Runs Strict Limit Models

This repository contains training data and model artifacts from Tree of Thoughts (TOT) experimental runs with strict limits.

๐Ÿ“Š Repository Statistics
  • Total Size : 0.0 GB (0.0 MB)
  • Total Files : 253
  • Checkpoint Files : 38
  • Metadata Files : 186
  • Result Files : 25
  • Last Updated : 2025-08-01 09:26:43
๐Ÿ—‚๏ธ Repository Structure
โ”œโ”€โ”€ checkpoints/          # Model checkpoints and weights (38 files)
โ”‚   โ”œโ”€โ”€ run_1753687216/   # First experimental run
โ”‚   โ”œโ”€โ”€ run_1753689856/   # Second experimental run  
โ”‚   โ””โ”€โ”€ run_1753693413/   # Third experimental run
โ”œโ”€โ”€ metadata/             # Configuration files, logs, and metadata (186 files)
โ”‚   โ”œโ”€โ”€ run_1753687216/   # Configuration and logs for first run
โ”‚   โ”œโ”€โ”€ run_1753689856/   # Configuration and logs for second run
โ”‚   โ””โ”€โ”€ run_1753693413/   # Configuration and logs for third run
โ”œโ”€โ”€ results/              # Experimental results and analysis data (25 files)
โ”‚   โ”œโ”€โ”€ run_1753687216/   # Results from first run
โ”‚   โ”œโ”€โ”€ run_1753689856/   # Results from second run
โ”‚   โ””โ”€โ”€ run_1753693413/   # Results from third run
โ””โ”€โ”€ README.md            # This file
๐Ÿงช Experimental Runs
Overview

This repository contains artifacts from three experimental runs of Tree of Thoughts (TOT) models with strict computational limits:

  • Run 1753687216 : Experimental run with strict resource constraints
  • Run 1753689856 : Follow-up experimental run with optimized parameters
  • Run 1753693413 : Final experimental run with refined approach
Methodology

These runs were conducted with strict computational limits to evaluate the performance and efficiency of Tree of Thoughts approaches under resource constraints. Each run includes:

  • Model checkpoints at various training stages
  • Comprehensive metadata and configuration files
  • Detailed experimental results and metrics
  • Training logs and performance analytics
๐Ÿ“ Contents
Checkpoints Directory (38 files)

Contains model weights, optimizer states, and training checkpoints from each experimental run. Files include:

  • *.pt , *.pth - PyTorch model files
  • *.ckpt - Training checkpoints
  • *.safetensors - SafeTensors format model weights
  • *.pkl - Serialized model components and metadata
Metadata Directory (186 files)

Contains configuration files, training logs, and experimental metadata:

  • *.json , *.yaml - Configuration files
  • *.log , *.txt - Training and evaluation logs
  • *.pkl - Serialized configuration and parameter objects
  • Hyperparameter settings and experimental conditions
Results Directory (25 files)

Contains experimental results, metrics, and analysis data:

  • *.csv - Tabulated results and metrics
  • *.pkl , *.pickle - Serialized Python objects with results
  • *.npy , *.npz - NumPy arrays with numerical results
  • Performance analytics and comparative studies
๐Ÿ“ˆ File Type Distribution
  • .json : 137 files
  • .pkl : 25 files
  • .txt : 22 files
  • .pt : 19 files
  • .safetensors : 19 files
  • .jinja : 19 files
  • .jsonl : 10 files
  • .md : 1 files
๐Ÿš€ Usage

To download and use these models:

from huggingface_hub import snapshot_download

# Download entire repository
repo_path = snapshot_download(repo_id="ziadrone/tot_runs_strict_limit_models")

# Download specific run
run_1_path = snapshot_download(
    repo_id="ziadrone/tot_runs_strict_limit_models",
    allow_patterns="checkpoints/run_1753687216/**"
)

# Load metadata for analysis
import pickle
with open("metadata/run_1753687216/metadata.pkl", "rb") as f:
    metadata = pickle.load(f)
๐Ÿ”ฌ Research Applications

These experimental artifacts are suitable for:

  • Comparative analysis of Tree of Thoughts approaches
  • Resource-constrained model training research
  • Computational efficiency studies
  • Reproducibility studies in AI research
  • Educational purposes in advanced ML courses
๐Ÿ“Š Technical Specifications
  • Framework : PyTorch
  • Model Type : Tree of Thoughts (TOT)
  • Training Regime : Strict computational limits
  • Artifact Types : Checkpoints, metadata, results
  • Storage Format : Mixed (PyTorch, Pickle, NumPy)
  • Total Storage : 0.0 GB
๐Ÿ“š Citation

If you use these models or results in your research, please cite:

@misc{tot_runs_strict_limit_2025,
  title={Tree of Thoughts Experimental Runs with Strict Limits},
  author={ZiaDrone},
  year={2025},
  howpublished={\url{https://huggingface.co/ziadrone/tot_runs_strict_limit_models}}
}
๐Ÿ“„ License

This repository is licensed under the Apache 2.0 License. Please refer to individual model files and documentation for specific licensing information.

๐Ÿค Contact

For questions about these experimental runs, please open an issue in this repository or contact the maintainer.


Repository created on 2025-08-01
Total size: 0.0 GB | Files: 253 | Last updated: 2025-08-01 09:26:43

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