Instructions to use hf-internal-testing/tiny-random-SiglipModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SiglipModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="hf-internal-testing/tiny-random-SiglipModel") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SiglipModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-internal-testing/tiny-random-SiglipModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 409 Bytes
5f4a673 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"eos_token": {
"content": "</s>",
"lstrip": true,
"normalized": false,
"rstrip": true,
"single_word": false
},
"pad_token": {
"content": "</s>",
"lstrip": true,
"normalized": false,
"rstrip": true,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": true,
"normalized": false,
"rstrip": true,
"single_word": false
}
}
|