Instructions to use EduardoPacheco/imagebind-huge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EduardoPacheco/imagebind-huge with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EduardoPacheco/imagebind-huge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from EduardoPacheco/imagebind-huge: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/EduardoPacheco/imagebind-huge/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://EduardoPacheco/imagebind-huge/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/EduardoPacheco/imagebind-huge/resolve/main/preprocessor_config.json
401 Bytes
| { | |
| "chunk_duration": 2.0, | |
| "do_chunk": true, | |
| "do_normalize": true, | |
| "feature_extractor_type": "ImageBindFeatureExtractor", | |
| "feature_size": 1, | |
| "max_length": 204, | |
| "mean": -4.268, | |
| "num_chunks": 3, | |
| "num_mel_bins": 128, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "ImageBindProcessor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000, | |
| "std": 9.138 | |
| } | |