Instructions to use Salesforce/blip2-itm-vit-g-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-itm-vit-g-coco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Salesforce/blip2-itm-vit-g-coco") 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("Salesforce/blip2-itm-vit-g-coco") model = AutoModelForZeroShotImageClassification.from_pretrained("Salesforce/blip2-itm-vit-g-coco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Salesforce/blip2-itm-vit-g-coco: direct link, hf CLI and curl.
- Browser
- Download file 263 Bytes
-
https://huggingface.co/Salesforce/blip2-itm-vit-g-coco/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Salesforce/blip2-itm-vit-g-coco/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Salesforce/blip2-itm-vit-g-coco/resolve/main/special_tokens_map.json
263 Bytes
| { | |
| "bos_token": { | |
| "content": "[DEC]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |