🧠
Model

Mon Modele Avis

by ousmanee ousmanee/mon-modele-avis
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 92
Q: Quality 65
Tech Context
0.11B Params
4.096K Ctx
Vital Performance
14 DL / 30D

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 0.11B Params
4k Context
14 Downloads
8G GPU ~2GB Est. VRAM
Dense CAMEMBERTFORSEQUENCECLASSIFICATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID ousmanee/mon-modele-avis
License MIT
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{ousmanee_mon_modele_avis,
  author = {ousmanee},
  title = {Mon Modele Avis Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ousmanee/mon-modele-avis}},
  note = {Accessed via Free2AITools.}
}
APA Style
ousmanee. (2026). Mon Modele Avis [Model]. Free2AITools. https://huggingface.co/ousmanee/mon-modele-avis

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run mon-modele-avis
πŸ€— HF Download
huggingface-cli download ousmanee/mon-modele-avis
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 2
Recency (R) 92
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Mon Modele Avis: Authority (A:0), Popularity (P:2), Recency (R:92), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

Open data Updated: Live data
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πŸš€ What's Next?

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
14Downloads
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--ousmanee--mon-modele-avis
slug
ousmanee--mon-modele-avis
source
huggingface
author
ousmanee
license
MIT
tags
transformers, safetensors, camembert, text-classification, generated_from_trainer, base_model:almanach/camembert-base, base_model:finetune:almanach/camembert-base, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
CamembertForSequenceClassification
params billions
0.11
context length
4,096
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
14
stars
null
forks
null

Data indexed from public sources. Updated daily.