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xlm-roberta-base

The XLM-RoBERTa model is a multilingual version of RoBERTa, pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper "Unsupervised Cross-lingual Representation Learning at Scale" by Conneau et al. and first released in this repository. The model learns an inner representation of 100 languages that can be used to extract features useful for downstream tasks.

The XLM-RoBERTa model is a multilingual version of RoBERTa, pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper "Unsupervised Cross-lingual Representation Learning at Scale" by Conneau et al. and first released in this repository. The model learns an inner representation of 100 languages that can be used to extract features useful for downstream tasks.

Public
$0.0005 / sec

HTTP/cURL API

You can use cURL or any other http client to run inferences:

curl -X POST \
    -d '{"input": "Where is my <mask>?"}'  \
    -H "Authorization: bearer $DEEPINFRA_TOKEN"  \
    -H 'Content-Type: application/json'  \
    'https://api.deepinfra.com/v1/inference/xlm-roberta-base'

which will give you back something similar to:

{
  "results": [
    {
      "sequence": "where is my father?",
      "score": 0.08898820728063583,
      "token": 2269,
      "token_str": "father"
    },
    {
      "sequence": "where is my mother?",
      "score": 0.07864926755428314,
      "token": 2388,
      "token_str": "mother"
    }
  ],
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

Input fields

inputstring

text prompt, should include exactly one <mask> token


webhookfile

The webhook to call when inference is done, by default you will get the output in the response of your inference request

Input Schema

Output Schema