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Bidirlm Omni 2.5b Embedding model by BidirLM
⭐ 45
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Model

Bidirlm Omni 2.5b Embedding

by BidirLM bidirlm/bidirlm-omni-2.5b-embedding
Free2AITools Nexus Index
45.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 51
P: Popularity 43
R: Recency 80
Q: Quality 65
Tech Context
2.45 Params
4.096K Ctx
Vital Performance
8.3K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 45 FNI Score
Tiny 2.45B Params
4k Context
8.3K Downloads
8G GPU ~4GB Est. VRAM
Dense BIDIRLM_OMNI Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID bidirlm/bidirlm-omni-2.5b-embedding
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~3.1GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_dataset_bidirlm_bidirlm_omni_2_5b_embedding,
  author = {BidirLM},
  title = {Bidirlm Omni 2.5b Embedding Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/BidirLM/BidirLM-Omni-2.5B-Embedding}},
  note = {Accessed via Free2AITools.}
}
APA Style
BidirLM. (2026). Bidirlm Omni 2.5b Embedding [Model]. Free2AITools. https://huggingface.co/BidirLM/BidirLM-Omni-2.5B-Embedding

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run bidirlm-omni-2.5b-embedding
πŸ€— HF Download
huggingface-cli download bidirlm/bidirlm-omni-2.5b-embedding
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) 51
Popularity (P) 43
Recency (R) 80
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Bidirlm Omni 2.5b Embedding: Authority (A:51), Popularity (P:43), Recency (R:80), 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
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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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
8.3KDownloads
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-dataset--bidirlm--bidirlm-omni-2.5b-embedding
slug
bidirlm--bidirlm-omni-2.5b-embedding
source
huggingface
author
BidirLM
license
Apache-2.0
tags
sentence-transformers, safetensors, bidirlm_omni, mteb, transformers, embedding, bidirectional, multilingual, sentence-similarity, custom_code, af, am, ar, az, be, bg, bn, bs, ca, ceb, cs, cy, da, de, el, en, es, et, eu, fa, fi, fr, ga, gl, gu, ha, he, hi, hr, ht, hu, hy, id, ig, is, it, ja, jv, ka, kk, kn, ko, ky, lt, lv, mg, mk, ml, mr, ms, mt, my, nb, ne, nl, nso, ny, pa, pl, ps, pt, ro, ru, sd, si, sk, sl, sn, so, sq, sr, su, sv, sw, ta, te, th, tl, tr, uk, ur, vi, wo, xh, yo, zh, zu, datase

βš™οΈ Technical Specs

architecture
bidirlm_omni
params billions
2.45
context length
4,096
pipeline tag
sentence-similarity
vram gb
3.1
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
8,286
stars
null
forks
null

Data indexed from public sources. Updated daily.