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
| version: "3" | |
| tasks: | |
| default: | |
| desc: List all available tasks | |
| cmds: | |
| - task -l | |
| lint: | |
| desc: Run all linting checks | |
| cmds: | |
| - uv run ruff check src --fix --unsafe-fixes | |
| type: | |
| desc: Run type checker | |
| cmds: | |
| - find src/distiller -name "*.py" | xargs uv run mypy | |
| format: | |
| desc: Run all formatters | |
| cmds: | |
| - uv run ruff format src | |