🧠
Raidahandnawe Sentiment Model model by RaidahAhmed
⭐ 46.3
🧠
Model

Raidahandnawe Sentiment Model

by RaidahAhmed raidahahmed/raidahandnawe-sentiment-model
Free2AITools Nexus Index
46.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 5
R: Recency 98
Q: Quality 65
Tech Context
0.07B Params
512 Ctx
Vital Performance
47 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 46.3 FNI Score
Tiny 0.07B Params
1k Context
47 Downloads
8G GPU ~2GB Est. VRAM
Dense DISTILBERTFORSEQUENCECLASSIFICATION Architecture
Model Information Summary
Entity Passport
Registry ID raidahahmed/raidahandnawe-sentiment-model
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{raidahahmed_raidahandnawe_sentiment_model,
  author = {RaidahAhmed},
  title = {Raidahandnawe Sentiment Model Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/RaidahAhmed/RaidahandNawe-sentiment-model}},
  note = {Accessed via Free2AITools.}
}
APA Style
RaidahAhmed. (2026). Raidahandnawe Sentiment Model [Model]. Free2AITools. https://huggingface.co/RaidahAhmed/RaidahandNawe-sentiment-model

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run raidahandnawe-sentiment-model
πŸ€— HF Download
huggingface-cli download raidahahmed/raidahandnawe-sentiment-model

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 29
Popularity (P) 5
Recency (R) 98
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Raidahandnawe Sentiment Model: Authority (A:29), Popularity (P:5), Recency (R:98), 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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⚠️ 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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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
47Downloads
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--raidahahmed--raidahandnawe-sentiment-model
slug
raidahahmed--raidahandnawe-sentiment-model
source
huggingface
author
RaidahAhmed
tags
safetensors, distilbert, sentiment-analysis, text-classification, en, region:us

βš™οΈ Technical Specs

architecture
DistilBertForSequenceClassification
params billions
0.07
context length
512
pipeline tag
text-classification
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
47

Data indexed from public sources. Updated daily.