Feature Extraction
sentence-transformers
ONNX
Safetensors
OpenVINO
Transformers
Transformers.js
English
bert
mteb
sentence_embedding
feature_extraction
Eval Results (legacy)
text-embeddings-inference
Instructions to use WhereIsAI/UAE-Large-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use WhereIsAI/UAE-Large-V1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("WhereIsAI/UAE-Large-V1") 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 WhereIsAI/UAE-Large-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="WhereIsAI/UAE-Large-V1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WhereIsAI/UAE-Large-V1") model = AutoModel.from_pretrained("WhereIsAI/UAE-Large-V1") - Transformers.js
How to use WhereIsAI/UAE-Large-V1 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'WhereIsAI/UAE-Large-V1'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 135a2654c1713d82f82f0bb76ef2da3c58e8b872ef32e9b5c0852ee225096c43
- Size of remote file:
- 337 MB
- SHA256:
- b2c10399acd8acaa6e390d5cddde9e0c16581d393b63915a2fe8d280b4d9119d
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