ShauryaNova/autotrain-rp16o-pxwa0

library_name: sentence-transformers tags:

• —sentence-transformers
• —sentence-similarity
• —feature-extraction
• —autotrain base_model: sentence-transformers/all-MiniLM-L6-v2 widget:
• —sourcesentence: 'searchquery: i love autotrain' sentences:
• —'search_query: huggingface auto train'
• —'search_query: hugging face auto train'
• —'searchquery: i love autotrain' pipelinetag: sentence-similarity ---

Model Trained Using AutoTrain

• —Problem type: Sentence Transformers

Validation Metrics

loss: 0.056603044271469116

cosine_accuracy: 1.0

dot_accuracy: 0.0

manhattan_accuracy: 1.0

euclidean_accuracy: 1.0

max_accuracy: 1.0

runtime: 43.9603

samplespersecond: 13.194

stepspersecond: 0.842

: 3.0

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the Hugging Face Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
    'search_query: autotrain',
    'search_query: auto train',
    'search_query: i love autotrain',
]
embeddings = model.encode(sentences)
print(embeddings.shape)

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)