#Be sure to have git-lfs installed (https://git-lfs.com) git lfs install git clone https://huggingface.co/sentence-transformers/all-mpnet-base-v2 #To clone the repo without large files – just their pointers #prepend git clone with the following env var: GIT_LFS_SKIP_SMUDGE=1
Sentence-transformers/all-mpnet-base-v2 model: Difference between revisions
(Created page with "{{Model infobox | hugging-face-uri = sentence-transformers/all-mpnet-base-v2 | creator = | type = Natural Language Processing, Multimodal | task = Sentence Similarity, Feature Extraction | library = PyTorch, 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/...") |
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==Model Description== | ==Model Description== | ||
==Comments== | |||
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==Clone Model Repository== | ==Clone Model Repository== | ||
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==Deployment== | ==Deployment== | ||
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===Amazon SageMaker=== | ===Amazon SageMaker=== | ||
===Spaces=== | ===Spaces=== | ||
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==Training== | ==Training== | ||
==Model Card== | ==Model Card== | ||
Revision as of 18:30, 21 May 2023
Hugging Face
Name
all-mpnet-base-v2
User / Organization
Library
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
License
Related to
Sentence-transformers/all-mpnet-base-v2 model is a Natural Language Processing, Multimodal model used for Sentence Similarity, Feature Extraction.
Model Description
Comments
Loading comments...
Clone Model Repository
#Be sure to have git-lfs installed (https://git-lfs.com) git lfs install git clone [email protected]:sentence-transformers/all-mpnet-base-v2 #To clone the repo without large files – just their pointers #prepend git clone with the following env var: GIT_LFS_SKIP_SMUDGE=1
Deployment
Inference API
import requests
API_URL = "https://api-inference.huggingface.co/models/sentence-transformers/all-mpnet-base-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-mpnet-base-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-mpnet-base-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}"
Amazon SageMaker
Spaces
import gradio as gr
gr.Interface.load("models/sentence-transformers/all-mpnet-base-v2").launch()