🧠
Dl2 Hw2 Bert Ner model by gzverev
⭐ 39
🧠
Model

Dl2 Hw2 Bert Ner

by gzverev gzverev/dl2-hw2-bert-ner
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 100
Q: Quality 65
Tech Context
0.03B Params
512 Ctx
Vital Performance
15 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 0.03B Params
1k Context
15 Downloads
8G GPU ~2GB Est. VRAM
Dense BERTFORTOKENCLASSIFICATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID gzverev/dl2-hw2-bert-ner
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{gzverev_dl2_hw2_bert_ner,
  author = {gzverev},
  title = {Dl2 Hw2 Bert Ner Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/gzverev/dl2-hw2-bert-ner}},
  note = {Accessed via Free2AITools.}
}
APA Style
gzverev. (2026). Dl2 Hw2 Bert Ner [Model]. Free2AITools. https://huggingface.co/gzverev/dl2-hw2-bert-ner

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run dl2-hw2-bert-ner
πŸ€— HF Download
huggingface-cli download gzverev/dl2-hw2-bert-ner
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 2
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Dl2 Hw2 Bert Ner: Authority (A:0), Popularity (P:2), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

Technical Deep Dive

⚠️ 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 β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.

Social Proof

HuggingFace Hub
15Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--gzverev--dl2-hw2-bert-ner
slug
gzverev--dl2-hw2-bert-ner
source
huggingface
author
gzverev
license
MIT
tags
transformers, safetensors, bert, token-classification, generated_from_trainer, base_model:baai/bge-small-en-v1.5, base_model:finetune:baai/bge-small-en-v1.5, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
BertForTokenClassification
params billions
0.03
context length
512
pipeline tag
token-classification
vram gb
1.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
15

Data indexed from public sources. Updated daily.