Sentence Similarity
sentence-transformers
Safetensors
Bengali
English
bert
feature-extraction
bangla
bengali
retrieval
cross-lingual
knowledge-distillation
text-embeddings-inference
Instructions to use kazalbrur/bangla-embed-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kazalbrur/bangla-embed-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kazalbrur/bangla-embed-e5-small") sentences = [ "সে একজন সুখী ব্যক্তি", "সে হ্যাপি কুকুর", "সে খুব সুখী মানুষ", "আজ একটি রৌদ্রোজ্জ্বল দিন" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Set license to MIT
Browse files
README.md
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
---
|
| 2 |
-
license:
|
| 3 |
language:
|
| 4 |
- bn
|
| 5 |
- en
|
|
@@ -66,9 +66,9 @@ This is an E5-family model: prefix queries with `query: ` and passages with `pas
|
|
| 66 |
|
| 67 |
Three-stage curriculum (AdamW, cosine schedule, bf16). Distillation over ~18.7M EN–BN parallel
|
| 68 |
pairs; supervised contrastive fine-tuning (MNR) on ~2.45M pairs (Bangla-native core + SWIM-IR +
|
| 69 |
-
machine-translated MS MARCO-bn); NLI triplet polish (XNLI-bn).
|
| 70 |
-
|
| 71 |
-
upstream terms before commercial deployment.
|
| 72 |
|
| 73 |
## Limitations
|
| 74 |
|
|
|
|
| 1 |
---
|
| 2 |
+
license: mit
|
| 3 |
language:
|
| 4 |
- bn
|
| 5 |
- en
|
|
|
|
| 66 |
|
| 67 |
Three-stage curriculum (AdamW, cosine schedule, bf16). Distillation over ~18.7M EN–BN parallel
|
| 68 |
pairs; supervised contrastive fine-tuning (MNR) on ~2.45M pairs (Bangla-native core + SWIM-IR +
|
| 69 |
+
machine-translated MS MARCO-bn); NLI triplet polish (XNLI-bn). Released under the **MIT license**.
|
| 70 |
+
Note that some training sources carry their own (in some cases non-commercial) terms — verify
|
| 71 |
+
upstream data terms before commercial deployment.
|
| 72 |
|
| 73 |
## Limitations
|
| 74 |
|