Nfero

Embedding

Text Embedding V4

Alibaba text embedding model for retrieval, search, and semantic indexing.

Alibaba CloudEmbeddingneeds review

Visual demos

Example media slots

Retrieval demo

Search relevance

Rank Qwen, Wan, and HappyHorse model pages for a developer searching for text-to-video.

Embedding slot

Vector match

Embed model descriptions and cluster them by task, cost, and hosted availability.

Rerank slot

Rerank result

Rerank enterprise coding models by reasoning, vision, and Token Plan compatibility.

These are safe placeholder slots. Swap in official Alibaba-provided logos, posters, and demo videos when asset usage is approved.

Inputs

Advanced settings

Cost

Unknown

Pricing has not been verified. Treat this model as needs_review for production use.

Unpriced usageNeeds review

Output

embedding
No run output yet.

License

Provider terms Commercial status: unknown.

Deployment

Endpoint payload needs admin adapter verification.

Limits

Limits need admin review.

API Examples

curl
curl -X POST https://nfero.com/api/models/text-embedding-v4/run \
  -H 'content-type: application/json' \
  -d '{"texts":["Nfero Model Hub","Alibaba Model Studio"],"normalize":true}'
JavaScript
await fetch('/api/models/text-embedding-v4/run', {
  method: 'POST',
  headers: { 'content-type': 'application/json' },
  body: JSON.stringify({
  "texts": [
    "Nfero Model Hub",
    "Alibaba Model Studio"
  ],
  "normalize": true
})
});
Python
import requests
requests.post('https://nfero.com/api/models/text-embedding-v4/run', json={
  "texts": [
    "Nfero Model Hub",
    "Alibaba Model Studio"
  ],
  "normalize": true
})

Recent Runs

No runs recorded yet.

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