Instructions to use carsonpoole/binary-siglip-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carsonpoole/binary-siglip-text with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("carsonpoole/binary-siglip-text") model = AutoModel.from_pretrained("carsonpoole/binary-siglip-text") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| license: apache-2.0 | |
| library_name: transformers | |
| # Description | |
| This is a fine tuned `google/siglip-so400m-patch14-384` for the purpose of quantizing the embeddings to binary. | |
| It's only using the first 1024 embeddings, so if you use all 1152 of them your results will be less than desirable. | |
| I updated the model today (April 30th) and evals are much better than before, but I'm continuing training so perf should only get better from here. | |
| ## Evals | |
| Coming soon |