Medical NER (DeBERTa)
Token-classification model that extracts 41 medical entity types from clinical text, such as disease, medication, dosage, frequency, lab test, sign and symptom. Fine-tuned on a DeBERTa v3 base, which gives more accurate spans than older BERT-based taggers on the same corpus.
Medical NER (DeBERTa) is text & chat AI model from huggingface, priced at €0.000 per 1M input tokens with a unknown context window.
About this model
0.7
Pricing
API Integration
Use our OpenAI-compatible API to integrate Medical NER (DeBERTa) into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
// Simple — just pass a string
const reply = await rw.run("medical-ner-deberta", "Hello! What can you do?");
console.log(reply);
// With message history
const reply2 = await rw.run("medical-ner-deberta", [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);
// Full response with usage info
const res = await rw.chat("medical-ner-deberta", [
{ role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);Frequently asked questions
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