NER & Token Classification in Python | hjLabs.in
Verifiable proof

Proof You Can Open in a Browser Tab

Working systems you can open right now, without talking to us. There are no client logos below and no testimonials — we will not publish proof we cannot substantiate. What we can put in front of you is software hjLabs.in built, deployed and keeps running in public. Open it, push on it, and judge the engineering yourself before you spend time on a call.

The exact task, live

Named entity recognition in your browser, on your own GPU

139open models
running live

Paste your own text and run an open NER model on your own GPU via WebGPU. Nothing is uploaded. Extractive question answering sits beside it for the cases where a span is easier to pull with a question than with an entity type.

Entity detection where it has to be exact

DICOM viewer with a full PS3.15 PHI de-identifier

652attributes
implemented

We transcribed DICOM PS3.15 Annex E Table E.1-1 — the Basic Application Level Confidentiality Profile — in full: 652 attributes, each carrying the standard’s own action code and VR. De-identification overwrites element values in place at their existing byte offsets, so the rest of the file, pixel data included, stays byte-identical to the original. It runs entirely in your browser; the study is never uploaded.

Why hjLabs.in — stated plainly

We are a small specialist team, not a large consultancy, and we are not going to dress up as one. Here is what that actually buys you.

You talk to the engineer who builds it

There is no account-manager layer between you and the person writing the code. The engineer who takes your scoping call is the engineer on your project, and stays reachable for the length of it.

Industrial hardware is our background, not a slide

hjLabs.in designs, manufactures and sells production machines — CNC routing, selective soldering, wire cutting, spring coiling, transformer winding. When a vision model has to survive a real factory line, cameras, lighting, PLCs and vibration are our day job, not a subcontractor’s.

Our work is inspectable before you pay us

Live tools you can open, open-source repositories you can read, and a standards implementation you can check line by line against the DICOM specification. You do not have to take a claim on trust when you can go and test it.

What we are not going to show you: client logos, testimonials or case-study numbers. We will not publish proof we cannot substantiate, and we would rather you find that out on this page than after signing something. For a focused engagement, the trade is straightforward — less brand-name comfort, more of the senior engineering time you are paying for.

NER & Token Classification

Boost your business's decision-making with our expert services in named entity recognition (NER) and token classification, employing Python, Hugging Face, and spaCy. Our solutions process large volumes of unstructured text data, generating valuable insights for your business.

Our NER services identify and extract relevant entities like names, organizations, locations, and more from unstructured text data. Token classification, a vital aspect of information extraction, involves labeling tokens in text - empowering you to make data-driven decisions propelling your business forward.

Example Use Cases

📰 News Article NER

News agencies can employ our named entity recognition (NER) services using Python, Hugging Face, and SpaCy to analyze news articles and automatically identify and categorize entities, such as people, locations, and organizations. This can aid in content recommendation, summarization, and the generation of insights for better decision-making.

PythonHugging FacespaCy

🛒 E-commerce Product Token Classification

E-commerce platforms can benefit from our token classification services using BERT and PyTorch to analyze product descriptions and automatically identify and categorize entities, such as SKUs, MFRs, MPNs, and quantities. This enables enhanced product search, recommendation, and user sentiment analysis.

BERTPyTorchToken Classification

🩺 Healthcare Data NER

Healthcare organizations can leverage our NER with bidirectional LSTM-CNNs and token classification services to analyze medical records and research articles, enabling the automatic identification and categorization of entities such as patient names, symptoms, and treatment-related information.

LSTM-CNNsMedical NERClinical NLP

💹 Financial Data Token Classification

Financial institutions can employ our NLP and machine learning expertise to perform token classification on financial reports, news articles, and social media content, facilitating the automatic identification of entities like company names, stock symbols, and financial events.

NLPFinancial NLPMachine Learning

Why Choose Us?

check_circleAssisting in selecting or creating datasets tailored to your application
check_circleGuidance in choosing, training, and implementing ML models
check_circleExpert recommendations for appropriate inference and training hardware
check_circleEnhancing and optimizing your existing ML workflows
check_circleProficiency in Python, Machine Learning, NLP, and Deep Learning
check_circleDelivering high-quality, performance-driven solutions
check_circleProviding 24/7 support with ongoing assistance after project completion

Technologies Used

Our software services are powered by the following technologies:

PythonTensorFlowPyTorchKerasScikit-learnPandasNumPyspaCyNLTKHugging FaceXGBoostLightGBMCatBoostGensimFastTextOpenCVSciPyH2O.ai

Contact Us Today

Ready to get started? Contact our team of experts to discuss your token classification needs and discover how our services can help your business thrive.

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