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Deepseek Ocr model by lvyufeng
⭐ 37
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Model

Deepseek Ocr

by lvyufeng lvyufeng/deepseek-ocr
Free2AITools Nexus Index
37.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 9
R: Recency 61
Q: Quality 65
Tech Context
3.34 Params
4.096K Ctx
Vital Performance
112 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37 FNI Score
3.34B Params
4k Context
112 Downloads
8G GPU ~4GB Est. VRAM
Dense DEEPSEEKOCRFORCAUSALLM Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID lvyufeng/deepseek-ocr
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~3.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{lvyufeng_deepseek_ocr,
  author = {lvyufeng},
  title = {Deepseek Ocr Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/lvyufeng/DeepSeek-OCR}},
  note = {Accessed via Free2AITools.}
}
APA Style
lvyufeng. (2025). Deepseek Ocr [Model]. Free2AITools. https://huggingface.co/lvyufeng/DeepSeek-OCR

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run deepseek-ocr
πŸ€— HF Download
huggingface-cli download lvyufeng/deepseek-ocr
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) 33
Popularity (P) 9
Recency (R) 61
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Deepseek Ocr: Authority (A:33), Popularity (P:9), Recency (R:61), 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
112Downloads
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--lvyufeng--deepseek-ocr
slug
lvyufeng--deepseek-ocr
source
huggingface
author
lvyufeng
license
MIT
tags
transformers, safetensors, deepseek_vl_v2, feature-extraction, pytorch, mindspore, mindnlp, deepseek, vision-language, ocr, custom_code, image-text-to-text, multilingual, license:mit, region:us

βš™οΈ Technical Specs

architecture
DeepseekOCRForCausalLM
params billions
3.34
context length
4,096
pipeline tag
image-text-to-text
vram gb
3.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
112
stars
0
forks
0

Data indexed from public sources. Updated daily.