🧠
Model

Dynamic Alibi 2 4 256 Babylm 100m Epoch4

by Lanni Ni hf-model--lanni-ni--dynamic_alibi_2_4_256_babylm_100m_epoch4
Free2AITools Nexus Index
39.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 65
Tech Context
0.03B Params
4.096K Ctx
Vital Performance
27 DL / 30D
0.0%
Audited 39 FNI Score
Tiny 0.03B Params
4k Context
27 Downloads
8G GPU ~2GB Est. VRAM
Dense DYNAMICALIBIFORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID hf-model--lanni-ni--dynamic_alibi_2_4_256_babylm_100m_epoch4
Provider huggingface
💾

Compute Threshold

~1.3GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{hf_model__lanni_ni__dynamic_alibi_2_4_256_babylm_100m_epoch4,
  author = {Lanni Ni},
  title = {Dynamic Alibi 2 4 256 Babylm 100m Epoch4 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Lanni-ni/dynamic_alibi_2_4_256_babylm_100m_epoch4}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Lanni Ni. (2026). Dynamic Alibi 2 4 256 Babylm 100m Epoch4 [Model]. Free2AITools. https://huggingface.co/Lanni-ni/dynamic_alibi_2_4_256_babylm_100m_epoch4

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run dynamic_alibi_2_4_256_babylm_100m_epoch4
🤗 HF Download
huggingface-cli download lanni-ni/dynamic_alibi_2_4_256_babylm_100m_epoch4
đŸ“Ļ Install Lib
pip install -U transformers

âš–ī¸ Free2AITools Nexus Index V2.0

Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Dynamic Alibi 2 4 256 Babylm 100m Epoch4: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

Technical Deep Dive

âš 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.

View Original Source →

📝 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.

Social Proof

HuggingFace Hub
27Downloads
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseâ„šī¸ Verify with original source

đŸ›Ąī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--lanni-ni--dynamic_alibi_2_4_256_babylm_100m_epoch4
slug
lanni-ni--dynamic_alibi_2_4_256_babylm_100m_epoch4
source
huggingface
author
Lanni Ni
license
tags
transformers, safetensors, dynamic_alibi, text-generation, custom_code, arxiv:1910.09700, region:us

âš™ī¸ Technical Specs

architecture
DynamicAlibiForCausalLM
params billions
0.03
context length
4,096
pipeline tag
text-generation
vram gb
1.3
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
27
stars
0
forks
null

Data indexed from public sources. Updated daily.