gemma 3 1b it ocr denoising en

ProviderClemensK
Categoryspeech-enhancement
LicenseApache-2.0
Downloads6
Stars0

Overview

Gemma 3 1B IT OCR Denoising EN is a lightweight, instruction-tuned model specifically optimized for cleaning and refining OCR-generated text in English. Designed for developers handling noisy datasets from scanned documents or legacy PDFs, this model acts as a specialized post-processing layer to correct character misrecognitions and structural artifacts. Its 1B parameter footprint makes it ideal for edge deployment or integration into high-throughput pipelines where low latency is critical. Unlike general-purpose LLMs, this version is tuned for the specific nuances of OCR error correction, reducing the need for extensive prompt engineering to achieve clean, machine-readable text.

Highlights

  • Optimized for English OCR error correction and text denoising
  • Compact 1B parameter size for low-latency edge deployment
  • Instruction-tuned for precise, minimal-intervention text cleaning
  • Apache-2.0 license ensures flexible commercial integration
  • Reduces post-processing overhead for scanned document pipelines

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("ClemensK/gemma-3-1b-it-ocr-denoising-en")
tokenizer = AutoTokenizer.from_pretrained("ClemensK/gemma-3-1b-it-ocr-denoising-en")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download ClemensK/gemma-3-1b-it-ocr-denoising-en

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download ClemensK/gemma-3-1b-it-ocr-denoising-en config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('ClemensK/gemma-3-1b-it-ocr-denoising-en')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/ClemensK/gemma-3-1b-it-ocr-denoising-en

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/ClemensK/gemma-3-1b-it-ocr-denoising-en

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('ClemensK/gemma-3-1b-it-ocr-denoising-en')
tokenizer = AutoTokenizer.from_pretrained('ClemensK/gemma-3-1b-it-ocr-denoising-en')

Full Documentation

来源: HuggingFace

---
library_name: transformers
tags:

  • llama-factory

---

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