BioBERT v1.2 (Biomedical Embeddings)

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by Communitybiobert-base-cased-v1-2

DMIS-Lab (Korea University) BERT-base initialized from English BERT and further pretrained on PubMed abstracts. Used as a feature extractor it yields 768-dim contextual embeddings tuned for biomedical text mining tasks such as NER, relation extraction and biomedical question answering.

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Status: Unavailable
Context: 512 tokens
Input → output: Text → Vector
Developer: Community
Updated: September 23, 2026

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Text

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Biomedical text to embed

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Output

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About BioBERT v1.2 (Biomedical Embeddings)

TL;DRAs of September 23, 2026

BioBERT v1.2 (Biomedical Embeddings) is a model by Community in the Embeddings category. BioBERT v1.2 (Biomedical Embeddings) is currently not available on Railwail. The context window holds 512 tokens.

BioBERT continues pretraining of the cased English BERT-base model on large biomedical corpora (PubMed abstracts), keeping the original vocabulary so it stays compatible with general-domain BERT while gaining biomedical knowledge. Version 1.2 is the cased release maintained by DMIS-Lab. It was one of the first domain-adapted BERTs and remains a standard baseline for biomedical NLP. Served through Hugging Face with the feature-extraction pipeline, returning token-level hidden states; pool them for sentence or document embeddings.

Pricing

Currently unavailable. There is no price for this model at the moment, so it cannot be run.

API

Call BioBERT v1.2 (Biomedical Embeddings) with your Railwail API key. Use this model ID in the request:

biobert-base-cased-v1-2API documentation Get an API key

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The model has no verified price or is deactivated; API calls are refused.

Specifications

Model ID: biobert-base-cased-v1-2
Developer: Community
Category: Embeddings
Input: Text
Output: Vector
Context window: 512 tokens
Catalog entry updated: September 23, 2026

Input parameters

Inputs and settings from the model's input schema. The example in the API section shows which of them the API accepts.

ParameterTypeDefaultAllowed values

inputsrequired
Biomedical text to embed
Type: Text
Default: –
Allowed values: up to 4,000 characters

Use cases

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Frequently asked questions

What is BioBERT v1.2 (Biomedical Embeddings)?

BioBERT v1.2 (Biomedical Embeddings) is a model by Community in the Embeddings category. It is listed on Railwail but cannot be run at the moment.

How much does BioBERT v1.2 (Biomedical Embeddings) cost on Railwail?

BioBERT v1.2 (Biomedical Embeddings) cannot be run on Railwail at the moment, so there is no current price. Available alternatives with prices are listed further down this page.

What is the context window of BioBERT v1.2 (Biomedical Embeddings)?

The context window of BioBERT v1.2 (Biomedical Embeddings) holds 512 tokens.

How fast is BioBERT v1.2 (Biomedical Embeddings)?

There are not enough measured runs of BioBERT v1.2 (Biomedical Embeddings) on Railwail yet to state a run time. It depends on the input, the settings and the load at the provider.

Is BioBERT v1.2 (Biomedical Embeddings) better than OpenAI text-embedding-3-large?

That depends on the task. BioBERT v1.2 (Biomedical Embeddings) (Community) and OpenAI text-embedding-3-large (OpenAI) are both models in the Embeddings category. The comparison page shows their prices and specifications side by side.

Compare BioBERT v1.2 (Biomedical Embeddings) and OpenAI text-embedding-3-large

Can I use BioBERT v1.2 (Biomedical Embeddings) right now?

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