🧠
Opus Mt Tc Big En Pt model by Helsinki Nlp
⭐ 34.4
🧠
Model

Opus Mt Tc Big En Pt

by Helsinki Nlp helsinki-nlp/opus-mt-tc-big-en-pt
Free2AITools Nexus Index
34.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 50
P: Popularity 59
R: Recency 11
Q: Quality 65
Tech Context
0.23B Params
4.096K Ctx
Vital Performance
129.3K DL / 30D
Source β†’

Task categories from upstream metadata

✨Translation

Technical Constraints

Experimental / High Latency
Low FNI signal 34.4 FNI Score
Tiny 0.23B Params
4k Context
Hot 129.3K Downloads
8G GPU ~2GB Est. VRAM
Dense MARIANMTMODEL Architecture
Restricted CC License
Model Information Summary
Entity Passport
Registry ID helsinki-nlp/opus-mt-tc-big-en-pt
License CC-BY-4.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{helsinki_nlp_opus_mt_tc_big_en_pt,
  author = {Helsinki Nlp},
  title = {Opus Mt Tc Big En Pt Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-pt}},
  note = {Accessed via Free2AITools.}
}
APA Style
Helsinki Nlp. (2022). Opus Mt Tc Big En Pt [Model]. Free2AITools. https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-pt

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run opus-mt-tc-big-en-pt
πŸ€— HF Download
huggingface-cli download helsinki-nlp/opus-mt-tc-big-en-pt
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) 50
Popularity (P) 59
Recency (R) 11
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Opus Mt Tc Big En Pt: Authority (A:50), Popularity (P:59), Recency (R:11), 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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Deployment reference

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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.

Social Proof

HuggingFace Hub
129.3KDownloads
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-model--helsinki-nlp--opus-mt-tc-big-en-pt
slug
helsinki-nlp--opus-mt-tc-big-en-pt
source
huggingface
author
Helsinki Nlp
license
CC-BY-4.0
tags
transformers, pytorch, tf, safetensors, marian, text2text-generation, translation, opus-mt-tc, tc, big, en, pt, license:cc-by-4.0, model-index, endpoints_compatible, deploy:azure, region:us

βš™οΈ Technical Specs

architecture
MarianMTModel
params billions
0.23
context length
4,096
pipeline tag
translation
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
129,253
stars
0
forks
0

Data indexed from public sources. Updated daily.