Sentence Similarity
sentence-transformers
Safetensors
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use OneFly7/crossencoder_ep10_bs8_trans1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use OneFly7/crossencoder_ep10_bs8_trans1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("OneFly7/crossencoder_ep10_bs8_trans1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use OneFly7/crossencoder_ep10_bs8_trans1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("OneFly7/crossencoder_ep10_bs8_trans1") model = AutoModel.from_pretrained("OneFly7/crossencoder_ep10_bs8_trans1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 201 Bytes
8d22793 | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "3.0.1",
"transformers": "4.43.2",
"pytorch": "2.4.0+cu121"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": null
} |