Sentence Similarity
Transformers
ONNX
Safetensors
sentence-transformers
Transformers.js
English
new
feature-extraction
gte
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use Alibaba-NLP/gte-base-en-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alibaba-NLP/gte-base-en-v1.5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Alibaba-NLP/gte-base-en-v1.5", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use Alibaba-NLP/gte-base-en-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Alibaba-NLP/gte-base-en-v1.5", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers.js
How to use Alibaba-NLP/gte-base-en-v1.5 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'Alibaba-NLP/gte-base-en-v1.5'); - Notebooks
- Google Colab
- Kaggle
Update usage example with infinity
#13
by michaelfeil - opened
docker run --gpus all -v $PWD/data:/app/.cache -p "7997":"7997" \
michaelf34/infinity:0.0.68 \
v2 --model-id Alibaba-NLP/gte-base-en-v1.5 --revision "main" --dtype bfloat16 --batch-size 32 --device cuda --engine torch --port 7997
INFO: Started server process [1]
INFO: Waiting for application startup.
INFO 2024-11-12 23:40:58,030 infinity_emb INFO: infinity_server.py:89
Creating 1engines:
engines=['Alibaba-NLP/gte-base-en-v1.5']
INFO 2024-11-12 23:40:58,035 infinity_emb INFO: Anonymized telemetry.py:30
telemetry can be disabled via environment variable
`DO_NOT_TRACK=1`.
INFO 2024-11-12 23:40:58,042 infinity_emb INFO: select_model.py:64
model=`Alibaba-NLP/gte-base-en-v1.5` selected, using
engine=`torch` and device=`cuda`
INFO 2024-11-12 23:41:00,320 SentenceTransformer.py:216
sentence_transformers.SentenceTransformer
INFO: Load pretrained SentenceTransformer:
Alibaba-NLP/gte-base-en-v1.5
A new version of the following files was downloaded from https://huggingface.co/Alibaba-NLP/new-impl:
- configuration.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
A new version of the following files was downloaded from https://huggingface.co/Alibaba-NLP/new-impl:
- modeling.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
INFO 2024-11-12 23:43:33,218 infinity_emb INFO: Adding acceleration.py:56
optimizations via Huggingface optimum.
The class `optimum.bettertransformers.transformation.BetterTransformer` is deprecated and will be removed in a future release.
WARNING 2024-11-12 23:43:33,220 infinity_emb WARNING: acceleration.py:67
BetterTransformer is not available for model: <class
'transformers_modules.Alibaba-NLP.new-impl.40ced75c3
017eb27626c9d4ea981bde21a2662f4.modeling.NewModel'>
Continue without bettertransformer modeling code.
INFO 2024-11-12 23:43:33,469 infinity_emb INFO: Getting select_model.py:97
timings for batch_size=32 and avg tokens per
sentence=1
3.29 ms tokenization
6.17 ms inference
0.14 ms post-processing
9.60 ms total
embeddings/sec: 3332.34
INFO 2024-11-12 23:43:33,674 infinity_emb INFO: Getting select_model.py:103
timings for batch_size=32 and avg tokens per
sentence=512
16.20 ms tokenization
71.20 ms inference
0.21 ms post-processing
87.61 ms total
embeddings/sec: 365.26
thenlper changed pull request status to merged