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
Add infinity as example deployment
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README.md
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# Citation
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```
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## 3. Infinity
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[Infinity](https://github.com/michaelfeil/infinity) is a MIT licensed server for OpenAI-compatible deployment.
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```
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docker run --gpus all -v $PWD/data:/app/.cache -p "7997":"7997" \
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michaelf34/infinity:0.0.68 \
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v2 --model-id WhereIsAI/UAE-Large-V1 --revision "369c368f70f16a613f19f5598d4f12d9f44235d4" --dtype float16 --batch-size 32 --device cuda --engine torch --port 7997
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```
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# Citation
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