Instructions to use vidore/colpali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use vidore/colpali with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- sentence-transformers
How to use vidore/colpali with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vidore/colpali") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "transformer_task": "feature-extraction", | |
| "modality_config": { | |
| "text": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| }, | |
| "image": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| }, | |
| "message": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state", | |
| "format": "structured" | |
| } | |
| }, | |
| "module_output_name": "token_embeddings", | |
| "model_kwargs": { | |
| "key_mapping": { | |
| "^model\\.": "" | |
| } | |
| }, | |
| "processor_kwargs": { | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask", | |
| "token_type_ids" | |
| ] | |
| } | |
| } | |