| from transformers import pipeline | |
| import numpy | |
| # distilbert tasks | |
| # fill-mask | |
| # feature extraction | |
| # have to use more specific models/other models for other tasks | |
| #for mask gen | |
| unmasker = pipeline('fill-mask', model='distilbert-base-uncased', device=0) | |
| results = unmasker("I [MASK] today.", top_k=10) | |
| for prediction in results: | |
| print(f"Score: {prediction['score']:.4f} | Prediction: {prediction['sequence']}") | |
| #for feature extraction | |
| extractor = pipeline('feature-extraction', model='distilbert-base-uncased', device=0) | |
| results = extractor("Obama") | |
| #idk what this really does | |
| features = numpy.array(results) | |
| print(f"Shape: {features.shape}") |