Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
xlm-roberta
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/multilingual-e5-base") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
asdasd
#30
by kralbryan - opened
- .eval_results/ArguAna.yaml +0 -20
.eval_results/ArguAna.yaml
DELETED
|
@@ -1,20 +0,0 @@
|
|
| 1 |
-
- dataset:
|
| 2 |
-
id: mteb/arguana
|
| 3 |
-
task_id: ArguAna_default_test
|
| 4 |
-
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
|
| 5 |
-
value: 44.206
|
| 6 |
-
notes: Obtained using MTEB v1.12.75
|
| 7 |
-
source:
|
| 8 |
-
url: https://github.com/embeddings-benchmark/mteb/
|
| 9 |
-
name: Obtained using MTEB v1.12.75
|
| 10 |
-
user: mteb
|
| 11 |
-
- dataset:
|
| 12 |
-
id: mteb/arguana
|
| 13 |
-
task_id: ArguAna
|
| 14 |
-
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
|
| 15 |
-
value: 44.206
|
| 16 |
-
notes: Obtained using MTEB v1.12.75
|
| 17 |
-
source:
|
| 18 |
-
url: https://github.com/embeddings-benchmark/mteb/
|
| 19 |
-
name: Obtained using MTEB v1.12.75
|
| 20 |
-
user: mteb
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|