Sentence Similarity
sentence-transformers
PyTorch
roberta
feature-extraction
text-embeddings-inference
Instructions to use ncoop57/codeformer-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ncoop57/codeformer-java with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ncoop57/codeformer-java") 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] - Notebooks
- Google Colab
- Kaggle
ncoop57 commited on
Commit ·
ca3f7fa
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Parent(s): cc029d5
Update emission duration for more accurate estimate
Browse files- emissions.csv +1 -1
emissions.csv
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timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region
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2021-09-25T12:16:47,46c34b0f-ed69-46b9-a9d1-1b6143221d59,codecarbon,
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timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region
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2021-09-25T12:16:47,46c34b0f-ed69-46b9-a9d1-1b6143221d59,codecarbon,13500.53877806663513,0.006912246982896216,0.010193421659204857,United States,USA,,N,,
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