/sentence_similarity - Embedding Siyabasa Docs

**\
Returns 1 element

Python
Javascript
cURL

Python example:

from gradio_client import Client

client = Client("Remeinium/Embedding_Siyabasa")
result = client.predict(
    sentence1="මම පාසලට යමි",
    sentence2="ඔහු පාසලට යයි",
    api_name="/sentence_similarity"
)
print(json.dumps(result, indent=4))

from gradio_client import Client

client = Client("Remeinium/Embedding_Siyabasa")
result = client.predict(
	sentence1="මම පාසලට යමි",
	sentence2="ඔහු පාසලට යයි",
	api_name="/sentence_similarity"
)
print(result)

curl -X POST https://remeinium-embedding-siyabasa.hf.space/gradio_api/call/sentence_similarity -s -H "Content-Type: application/json" -d '{
	"data": ["මම පාසලට යමි",
			"ඔහු පාසලට යයි"
			]}' \
	| awk -F'"' '{ print $4}'  \
	| read EVENT_ID; curl -N https://remeinium-embedding-siyabasa.hf.space/gradio_api/call/sentence_similarity/$EVENT_ID

Response format:

{
    "sentence1": "මම පාසලට යමි",
    "sentence2": "ඔහු පාසලට යයි", 
    "similarity": 0.734567,
    "model": "UgannA_SiyabasaV2"
}

**\

Accepts 2 parameters:**

sentence1 : str *Required
The input value that is provided in the “Sentence A” Textbox component.
sentence2 : str *Required
The input value that is provided in the “Sentence B” Textbox component.

Returns 1 element

str | float | bool | list | dict

The output value that appears in the “Sentence Similarity” Json component.

/sentence_embedding

Document Search

⌘I