mandarjoshi/trivia_qa
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How to use cuteo23/scam_finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("cuteo23/scam_finetuned")
sentences = [
"The weather is lovely today.",
"It's so sunny outside!",
"He drove to the stadium."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]How to use cuteo23/scam_finetuned with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="cuteo23/scam_finetuned") # Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("cuteo23/scam_finetuned")
model = AutoModel.from_pretrained("cuteo23/scam_finetuned")This model is fine-tuned from sentence-transformers/all-mpnet-base-v2. It was trained in pair with a custom classifier to predict scam/not scam scenarios.
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("cuteo23/scam_finetuned")
embeddings = model.encode(["Hello world"])
Base model
sentence-transformers/all-mpnet-base-v2