Feature Extraction
Safetensors
Model2Vec
sentence-transformers
code
distiller
code-search
code-embeddings
distillation
static-embeddings
tokenlearn
Instructions to use sarthak1/codemalt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use sarthak1/codemalt with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("sarthak1/codemalt") - sentence-transformers
How to use sarthak1/codemalt with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sarthak1/codemalt") 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
Sarthak commited on
Commit ·
0b74f1f
1
Parent(s): 0b87653
feat: 4 stage training, refinement failed for first 3
Browse files- config.json +0 -10
- model.safetensors +2 -2
config.json
CHANGED
|
@@ -1,13 +1,3 @@
|
|
| 1 |
{
|
| 2 |
-
"model_type": "model2vec",
|
| 3 |
-
"architectures": [
|
| 4 |
-
"StaticModel"
|
| 5 |
-
],
|
| 6 |
-
"tokenizer_name": "Alibaba-NLP/gte-Qwen2-7B-instruct",
|
| 7 |
-
"apply_pca": 512,
|
| 8 |
-
"apply_zipf": null,
|
| 9 |
-
"sif_coefficient": 0.0001,
|
| 10 |
-
"hidden_dim": 512,
|
| 11 |
-
"seq_length": 1000000,
|
| 12 |
"normalize": true
|
| 13 |
}
|
|
|
|
| 1 |
{
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
"normalize": true
|
| 3 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5e0637b8e0ebda234cfa40973b0c7291da2a43e9f9c19ec6033caf24cf6223cc
|
| 3 |
+
size 310567000
|