Feature Extraction
sentence-transformers
PyTorch
Dutch
roberta
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:483497
loss:SpladeLoss
loss:SparseMarginMSELoss
loss:FlopsLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sparse-encoder/splade-robbert-dutch-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sparse-encoder/splade-robbert-dutch-base-v1 with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("sparse-encoder/splade-robbert-dutch-base-v1") queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -233,7 +233,7 @@ You can finetune this model on your own dataset.
|
|
| 233 |
|
| 234 |
#### MTEB
|
| 235 |
|
| 236 |
-
To evaluate this model, we've evaluated it on [BelebeleRetrieval](https://arxiv.org/abs/2308.16884) and WikipediaRetrievalMultilingual: the two Dutch Retrieval tasks recommended by [MMTEB](https://huggingface.co/spaces/mteb/leaderboard).
|
| 237 |
|
| 238 |

|
| 239 |
|
|
|
|
| 233 |
|
| 234 |
#### MTEB
|
| 235 |
|
| 236 |
+
To evaluate this model, we've evaluated it on [BelebeleRetrieval](https://arxiv.org/abs/2308.16884) (nld-nld) and WikipediaRetrievalMultilingual (nld): the two Dutch Retrieval tasks recommended by [MMTEB](https://huggingface.co/spaces/mteb/leaderboard).
|
| 237 |
|
| 238 |

|
| 239 |
|