Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use mchochlov/codebert-base-cd-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mchochlov/codebert-base-cd-ft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mchochlov/codebert-base-cd-ft") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use mchochlov/codebert-base-cd-ft with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mchochlov/codebert-base-cd-ft") model = AutoModel.from_pretrained("mchochlov/codebert-base-cd-ft") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1e56e7803d9f8998fed8cdea0a32ad3690bd10b4806816cb1b26d7dc98ed918
- Size of remote file:
- 499 MB
- SHA256:
- d8825d52d9bf14c68dfc352976e4db59a9936ab055da75c9871f3f6ef714616f
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