Feature Extraction
sentence-transformers
PyTorch
ONNX
English
bert
splade++
document-expansion
sparse representation
bag-of-words
passage-retrieval
knowledge-distillation
document encoder
sparse-encoder
sparse
splade
text-embeddings-inference
Instructions to use prithivida/Splade_PP_en_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use prithivida/Splade_PP_en_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("prithivida/Splade_PP_en_v1") 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
Update config.json
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -7,7 +7,7 @@
|
|
| 7 |
"fusions": {}
|
| 8 |
},
|
| 9 |
"architectures": [
|
| 10 |
-
"
|
| 11 |
],
|
| 12 |
"attention_probs_dropout_prob": 0.1,
|
| 13 |
"classifier_dropout": null,
|
|
|
|
| 7 |
"fusions": {}
|
| 8 |
},
|
| 9 |
"architectures": [
|
| 10 |
+
"BertForMaskedLM"
|
| 11 |
],
|
| 12 |
"attention_probs_dropout_prob": 0.1,
|
| 13 |
"classifier_dropout": null,
|