Models / Embeddings / GTE ModernBERT base API
GTE ModernBERT base API
Embeddings
Text embedding and rerank models built on modernBERT, excelling in MTEB, LoCO, and COIR retrieval benchmarks.
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API Usage
How to use GTE ModernBERT baseModel CardPrompting GTE ModernBERT baseApplications & Use CasesGTE ModernBERT base API Usage
Endpoint
Alibaba-NLP/gte-modernbert-base
RUN INFERENCE
curl -X POST "https://api.together.xyz/v1/embeddings" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d {
"model": "Alibaba-NLP/gte-modernbert-base",
"input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
}'JSON RESPONSE
RUN INFERENCE
from together import Together
client = Together()
response = client.embeddings.create(
model="Alibaba-NLP/gte-modernbert-base",
input="Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)
print(response.data[0].embedding)JSON RESPONSE
RUN INFERENCE
import Together from "together-ai";
const together = new Together();
const response = await together.embeddings.create({
model: "Alibaba-NLP/gte-modernbert-base",
input: "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
});
console.log(response.data[0].embedding);JSON RESPONSE
Model Provider:
Alibaba-NLP
Type:
Embeddings
Variant:
Parameters:
149M
Deployment:
✔️ Serverless
Quantization
Context length:
Pricing:
$0.08
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Quickstart docs
Quickstart docs
How to use GTE ModernBERT base
Model details
Prompting GTE ModernBERT base
Applications & Use Cases
Looking for production scale? Deploy on a dedicated endpoint
Deploy GTE ModernBERT base on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
