🧠
Kho V2 Lex Fi Sv model by ossib
⭐ 24.3
🧠
Model

Kho V2 Lex Fi Sv

by ossib hf-model--ossib--kho-v2-lex-fi-sv
Nexus Index
24.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 11
Q: Quality 50
Tech Context
Vital Performance
3 DL / 30D
0.0%
Source →
Audited 24.3 FNI Score
Tiny - Params
- Context
3 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--ossib--kho-v2-lex-fi-sv
License Apache-2.0
Provider huggingface
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Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__ossib__kho_v2_lex_fi_sv,
  author = {ossib},
  title = {Kho V2 Lex Fi Sv Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ossib/kho-v2-lex-fi-sv}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
ossib. (2026). Kho V2 Lex Fi Sv [Model]. Free2AITools. https://huggingface.co/ossib/kho-v2-lex-fi-sv

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download ossib/kho-v2-lex-fi-sv
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
24.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 11
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Kho V2 Lex Fi Sv: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:11), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

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Technical Deep Dive

ossib/kho-v2-lex-fi-sv

This model is a fine-tuned version of Helsinki-NLP/opus-mt-fi-sv on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.7801
  • Validation Loss: 0.9411
  • Epoch: 2

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2727, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: mixed_float16

Training results

Train Loss Validation Loss Epoch
1.1488 0.9713 0
0.8948 0.9464 1
0.7801 0.9411 2

Framework versions

  • Transformers 4.28.1
  • TensorFlow 2.12.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3

⚠ī¸ 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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📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

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AI Summary: Based on Hugging Face metadata. Not a recommendation.

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🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--ossib--kho-v2-lex-fi-sv
slug
ossib--kho-v2-lex-fi-sv
source
huggingface
author
ossib
license
Apache-2.0
tags
transformers, tf, marian, text2text-generation, generated_from_keras_callback, translation, fi, sv, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
translation

📊 Engagement & Metrics

downloads
3
stars
0
forks
0

Data indexed from public sources. Updated daily.