| from transformers import CLIPModel, CLIPProcessor |
| import torch |
| import numpy as np |
|
|
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| model = CLIPModel.from_pretrained(".").to(device) |
| processor = CLIPProcessor.from_pretrained(".") |
|
|
| def inference(inputs): |
| text = inputs.get("text", None) |
|
|
| if text: |
| processed = processor(text=[text], return_tensors="pt", truncation=True).to(device) |
| with torch.no_grad(): |
| emb = model.get_text_features(**processed) |
| emb = torch.nn.functional.normalize(emb, dim=-1) |
| return emb.cpu().numpy().tolist() |
|
|
| return {"error": "No valid input provided"} |
