The CLIP model was developed by OpenAI to investigate the robustness of computer vision models. It uses a Vision Transformer architecture and was trained on a large dataset of image-caption pairs. The model shows promise in various computer vision tasks but also has limitations, including difficulties with fine-grained classification and potential biases in certain applications.

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

```bash
curl -X POST \
    -H "Authorization: bearer $(deepctl auth token)"  \
    -F image=@my_image.jpg  \
    -F 'candidate_labels=["cat","dog"]'  \
    'https://api.deepinfra.com/v1/inference/openai/clip-vit-base-patch32'
```

which will give you back something similar to:

```json
{
  "results": [
    {
      "label": "dog",
      "score": 0.9
    },
    {
      "label": "cat",
      "score": 0.1
    }
  ],
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

```


You can use our command-line tool [deepctl](/docs/getting-started) to run
inferences:

```bash
deepctl infer \
    -m 'openai/clip-vit-base-patch32'  \
    -i image=@my_image.jpg  \
    -i 'candidate_labels=["cat","dog"]'
```

which will give you back something similar to:

```json
{
  "results": [
    {
      "label": "dog",
      "score": 0.9
    },
    {
      "label": "cat",
      "score": 0.1
    }
  ],
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

```


image

candidate_labels

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

webhook

Candidate Labels

Image

Webhook

ZeroShotImageClassificationIn

Label

Score

Item

estimated cost billed for the request in USD

Cost

Runtime Ms

Status

Tokens Generated

Tokens Input

Object containing the status of the inference request

Inference Status

Request Id

a list of top classifications, ordered by score

openai/clip-vit-base-patch32

Input

Output