Instructions to use noamrot/FuseCap_Image_Captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noamrot/FuseCap_Image_Captioning with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="noamrot/FuseCap_Image_Captioning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("noamrot/FuseCap_Image_Captioning") model = AutoModelForMultimodalLM.from_pretrained("noamrot/FuseCap_Image_Captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from noamrot/FuseCap_Image_Captioning: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/noamrot/FuseCap_Image_Captioning/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://noamrot/FuseCap_Image_Captioning/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/noamrot/FuseCap_Image_Captioning/resolve/main/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |