How to use from the
Use from the
sentence-transformers library
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("MaxNoichl/gte-modernbert-philosophy-v1-1-autotr")

sentences = [
    "search_query: i love autotrain",
    "search_query: huggingface auto train",
    "search_query: hugging face auto train",
    "search_query: i love autotrain"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Model Trained Using AutoTrain

  • Problem type: Sentence Transformers

Validation Metrics

loss: 0.4268312156200409

cosine_accuracy: 0.9693415637860082

runtime: 40.9588

samples_per_second: 118.656

steps_per_second: 7.422

: 1.0

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)
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