I have deployed sentence-transformers/all-MiniLM-L6-v2 on an Azure instance and the endpoint does not work.
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I tested on the end point page itself and it threw an error “API Implementation Error: Invalid output: output must be of type Array”. I gathered from this error that maybe the output in not in an expected format but there is an output. So I thought let me check what the output format is. (screenshot 1)
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I ran the cURL code on an online cURL executor and this time I got a blank response. (screenshot 2)
Can someone please point out what I may be doing wrong here.
@sid-050175 Hello. Could you resolve your problem? I am having the exact same problem, using the same model for computing sentence similarity.
Hi, no I could not. Still trying to trouble shoot. I wrote to hugging face support but haven’t heard back from them yet. If you have any joy, please do tell me
Sid
I could solve it in the meantime. Funnily it only works when using programmatically, not from the UI.
from dotenv import load_dotenv
load_dotenv()
import os
import requests
from requests.adapters import HTTPAdapter
def get_similarity(string1, string2):
API_URL = XXX
headers = {
"Authorization": f"Bearer {os.getenv('HF_API_KEY')}",
"Content-Type": "application/json"
}
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload, timeout=5)
return response.json()
output = query({
"inputs": {
"source_sentence": string1,
"sentences": [
string2
]
},
})
# print(output)
return output
if __name__ =='__main__':
output = get_similarity("I like apples", "I like oranges")
print(output)
Thanks, will give it a shot
Sid