README.md

---
license: cc-by-nc-sa-4.0
tags:
  - sentence-transformers
  - transformers
  - splade
  - sparse-encoder
  - code
pipeline_tag: feature-extraction
---

SPLADE-Code-06B is a sparse retrieval model designed for code retrieval tasks. It is the top-performing models on MTEB for models below 1B (at time of writing, Feb 2026).

## Usage

### Using Sentence Transformers

Install Sentence Transformers:
```bash
pip install sentence_transformers
```

```python
from sentence_transformers import SparseEncoder

model = SparseEncoder("naver/splade-code-06B", trust_remote_code=True)

queries = [
    "SELECT *\nFROM Student\nWHERE Age = (\nSELECT MAX(Age)\nFROM Student\nWHERE Group = 'specific_group'\n)\nAND Group = 'specific_group';"
]

query_embeddings = model.encode(queries)
print(query_embeddings.shape)
# torch.Size([1, 151936])

sparsity = model.sparsity(query_embeddings)
print(sparsity)
# {'active_dims': 1231.0, 'sparsity_ratio': 0.991897904380792}

decoded = model.decode(query_embeddings, top_k=10)
print(decoded)
# [[
#     ("Ġgroup", 2.34375),
#     ("Ġage", 2.34375),
#     ("ĠAge", 2.34375),
#     ("ĠStudent", 2.296875),
#     ("Ġspecific", 2.296875),
#     ("_group", 2.296875),
#     ("ĠMax", 2.21875),
#     ("Ġmax", 2.21875),
#     ("Ġstudent", 2.203125),
#     ("ĠGroup", 2.1875),
# ]]
```

### Using Transformers

```bash
pip install transformers
```

```python
from transformers import AutoModelForCausalLM, AutoModel
import os
import torch

splade = AutoModelForCausalLM.from_pretrained("naver/splade-code-06B", trust_remote_code=True)
device = (torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu"))
splade.to(device)
splade.eval()
queries = ["SELECT *\nFROM Student\nWHERE Age = (\nSELECT MAX(Age)\nFROM Student\nWHERE Group = 'specific_group'\n)\nAND Group = 'specific_group';"]
bow_dict = splade.encode(queries, prompt_type="query", top_k_q=10, return_dict=True, print_dict=True)
```

```
+--------------------------------------------------------------------+
|                        TOP ACTIVATED WORDS                         |
+--------------------------------------------------------------------+


* INPUT: SELECT *
FROM Student
WHERE Age = (
SELECT MAX(Age)
FROM Student
WHERE Group = 'specific_group'
)
AND Group = 'specific_group';

Ġgroup                    | ████████████████████ 2.34
Ġage                      | ███████████████████ 2.33
ĠAge                      | ███████████████████ 2.33
_group                    | ███████████████████ 2.30
ĠStudent                  | ███████████████████ 2.30
Ġspecific                 | ███████████████████ 2.28
Ġmax                      | ██████████████████ 2.22
ĠMax                      | ██████████████████ 2.22
Ġstudent                  | ██████████████████ 2.20
ĠGroup                    | ██████████████████ 2.19
```