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
File size: 361 Bytes
473c3a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from distiller.model2vec.utils import importable
importable("transformers", "tokenizer")
from distiller.model2vec.tokenizer.tokenizer import (
clean_and_create_vocabulary,
create_tokenizer,
replace_vocabulary,
turn_tokens_into_ids,
)
__all__ = ["clean_and_create_vocabulary", "create_tokenizer", "replace_vocabulary", "turn_tokens_into_ids"]
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