🧠
My Awesome Eli5 Clm Model model by ConnorBrug
⭐ 37
🧠
Model

My Awesome Eli5 Clm Model

by ConnorBrug hf-model--connorbrug--my_awesome_eli5_clm-model
Nexus Index
37.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 97
Q: Quality 65
Tech Context
Vital Performance
0 DL / 30D
0.0%
Source →
Audited 37 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--connorbrug--my_awesome_eli5_clm-model
License Apache-2.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__connorbrug__my_awesome_eli5_clm_model,
  author = {ConnorBrug},
  title = {My Awesome Eli5 Clm Model Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/connorbrug/my_awesome_eli5_clm-model}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
ConnorBrug. (2026). My Awesome Eli5 Clm Model [Model]. Free2AITools. https://huggingface.co/connorbrug/my_awesome_eli5_clm-model

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download connorbrug/my_awesome_eli5_clm-model
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
37.0
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 97
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for My Awesome Eli5 Clm Model: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:97), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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Deployment Guide

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Technical Deep Dive

my_awesome_eli5_clm-model

This model is a fine-tuned version of distilbert/distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.8065

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss
3.9196 1.0 1308 3.8161
3.8208 2.0 2616 3.8072
3.7816 3.0 3924 3.8065

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

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📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
🤗 Data Source: Hugging Face ↗
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AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--connorbrug--my_awesome_eli5_clm-model
slug
connorbrug--my_awesome_eli5_clm-model
source
huggingface
author
ConnorBrug
license
Apache-2.0
tags
transformers, safetensors, gpt2, text-generation, generated_from_trainer, base_model:distilbert/distilgpt2, base_model:finetune:distilbert/distilgpt2, license:apache-2.0, text-generation-inference, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
text-generation

📊 Engagement & Metrics

downloads
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stars
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