Sentence-transformers/all-MiniLM-L6-v2 model

Sentence-transformers/all-MiniLM-L6-v2 model

Hugging Face

sentence-transformers/all-MiniLM-L6-v2

Name

all-MiniLM-L6-v2

User / Organization

sentence-transformers

Type

Natural Language Processing, Multimodal

Task

Sentence Similarity, Feature Extraction

Library

PyTorch, TensorFlow, Rust, Sentence Transformers

Dataset

s2orc, flax-sentence-embeddings/stackexchange_xml, ms_marco, gooaq, yahoo_answers_topics, code_search_net, search_qa, eli5, snli, multi_nli, wikihow, natural_questions, trivia_qa, embedding-data/sentence-compression, embedding-data/flickr30k-captions, embedding-data/altlex, embedding-data/simple-wiki, embedding-data/QQP, embedding-data/SPECTER, embedding-data/PAQ_pairs, embedding-data/WikiAnswers

Language

English

License

arxiv:1904.06472, arxiv:2102.07033, arxiv:2104.08727, arxiv:1704.05179, arxiv:1810.09305, apache-2.0

Related to

bert

sentence-transformers Sentence Similarity, PyTorch, TensorFlow, Rust, Sentence Transformers, s2orc, flax-sentence-embeddings/stackexchange_xml, ms_marco, gooaq, yahoo_answers_topics, code_search_net, search_qa, eli5, snli, multi_nli, wikihow, natural_questions, trivia_qa, embedding-data/sentence-compression, embedding-data/flickr30k-captions, embedding-data/altlex, embedding-data/simple-wiki, embedding-data/QQP, embedding-data/SPECTER, embedding-data/PAQ_pairs, embedding-data/WikiAnswers, English, bert, feature-extraction, arxiv:1904.06472, arxiv:2102.07033, arxiv:2104.08727, arxiv:1704.05179, arxiv:1810.09305, License: apache-2.0 English

Sentence-transformers/all-MiniLM-L6-v2 model is a Natural Language Processing, Multimodal model used for Sentence Similarity, Feature Extraction.

Clone Model Repository

#Be sure to have git-lfs installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
  
#To clone the repo without large files – just their pointers
#prepend git clone with the following env var:
GIT_LFS_SKIP_SMUDGE=1

#Be sure to have git-lfs installed (https://git-lfs.com)
git lfs install
git clone [email protected]:sentence-transformers/all-MiniLM-L6-v2
  
#To clone the repo without large files – just their pointers
#prepend git clone with the following env var:
GIT_LFS_SKIP_SMUDGE=1

Hugging Face Transformers Library

undefined

Deployment

Inference API

import requests

API_URL = "https://api-inference.huggingface.co/models/sentence-transformers/all-MiniLM-L6-v2"
headers = {"Authorization": f"Bearer {API_TOKEN}"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.json()
	
output = query({
	"inputs": {
		"source_sentence": "That is a happy person",
		"sentences": [
			"That is a happy dog",
			"That is a very happy person",
			"Today is a sunny day"
		]
	},
})

async function query(data) {
	const response = await fetch(
		"https://api-inference.huggingface.co/models/sentence-transformers/all-MiniLM-L6-v2",
		{
			headers: { Authorization: "Bearer {API_TOKEN}" },
			method: "POST",
			body: JSON.stringify(data),
		}
	);
	const result = await response.json();
	return result;
}

query({"inputs": {
		"source_sentence": "That is a happy person",
		"sentences": [
			"That is a happy dog",
			"That is a very happy person",
			"Today is a sunny day"
		]
	}}).then((response) => {
	console.log(JSON.stringify(response));
});

curl https://api-inference.huggingface.co/models/sentence-transformers/all-MiniLM-L6-v2 \
	-X POST \
	-d '{"inputs": { "source_sentence": "That is a happy person", "sentences": [ "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] }}' \
	-H "Authorization: Bearer {API_TOKEN}"

Spaces

import gradio as gr

gr.Interface.load("models/sentence-transformers/all-MiniLM-L6-v2").launch()

Training