Instructions to use hf-internal-testing/tiny-random-XCLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-XCLIPModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XCLIPModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-XCLIPModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1104e48fd0fe43ffb1359c621c3b51ea285553d2c95b383975dda4c1c3e24c0e
- Size of remote file:
- 2.26 MB
- SHA256:
- 7f7ea4e88c47f3fe20983767a31f659bd4558b82eb11b159898b89b7068a3010
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