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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WhereIsAI/UAE-Large-V1") model = AutoModel.from_pretrained("WhereIsAI/UAE-Large-V1", device_map="auto") - 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'); - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -2596,4 +2596,13 @@ model-index:
|
|
| 2596 |
value: 86.33024314706873
|
| 2597 |
- type: max_f1
|
| 2598 |
value: 78.59623733719248
|
| 2599 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2596 |
value: 86.33024314706873
|
| 2597 |
- type: max_f1
|
| 2598 |
value: 78.59623733719248
|
| 2599 |
+
---
|
| 2600 |
+
|
| 2601 |
+
|
| 2602 |
+
# Universal AnglE Embedding
|
| 2603 |
+
|
| 2604 |
+
Our model is built upon the powerful BGE-Large, enhanced with [AnglE optimizing](https://github.com/SeanLee97/AnglE).
|
| 2605 |
+
|
| 2606 |
+
We will share our fine-tuning details later. Stay tuned:)
|
| 2607 |
+
|
| 2608 |
+
Welcome to follow [AnglE](https://github.com/SeanLee97/AnglE).
|