Add new SentenceTransformer model with an openvino backend
#5
by
ostoveland
- opened
Hello!
This pull request has been automatically generated from the push_to_hub
method from the Sentence Transformers library.
Full Model Architecture:
SentenceTransformer(
(0): Transformer({'max_seq_length': 75, 'do_lower_case': False}) with Transformer model: OVModelForFeatureExtraction
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)
Tip:
Consider testing this pull request before merging by loading the model from this PR with the revision
argument:
from sentence_transformers import SentenceTransformer
# TODO: Fill in the PR number
pr_number = 2
model = SentenceTransformer(
"ostoveland/SBertBaseMittanbudver3",
revision=f"refs/pr/{pr_number}",
backend="openvino",
)
# Verify that everything works as expected
embeddings = model.encode(["The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium."])
print(embeddings.shape)
similarities = model.similarity(embeddings, embeddings)
print(similarities)
ostoveland
changed pull request status to
merged