Sentence Similarity
sentence-transformers
Safetensors
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use djsull/sentence-roberta-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use djsull/sentence-roberta-multitask with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("djsull/sentence-roberta-multitask") 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
How to use djsull/sentence-roberta-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("djsull/sentence-roberta-multitask") model = AutoModel.from_pretrained("djsull/sentence-roberta-multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 968 Bytes
649aa1c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import os
import torch
from transformers import AutoModel, AutoTokenizer
from sentence_transformers import SentenceTransformer
from sagemaker_inference import content_types, decoder, default_inference_handler, encoder
def model_fn(model_dir):
model = SentenceTransformer(model_dir)
return model
def input_fn(request_body, request_content_type):
if request_content_type == content_types.JSON:
input_data = decoder.decode(request_body, content_types.JSON)
return input_data
else:
raise ValueError(f"Requested unsupported ContentType in content_type: {request_content_type}")
def predict_fn(input_data, model):
embeddings = model.encode(input_data)
return embeddings
def output_fn(prediction, accept):
if accept == content_types.JSON:
output = encoder.encode(prediction, content_types.JSON)
return output
else:
raise ValueError(f"Requested unsupported ContentType in Accept: {accept}")
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