How to use jameswright/ws-wr-questions-bert-TSDAE-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jameswright/ws-wr-questions-bert-TSDAE-v1") sentences = [ "it got and spoke was amazing and me sequi a month . I the been seen a in, I then started, im last one 4 ive my anxiety has horrible I have had a read of different and part hightened, didnt stright away the only just taised head the last . to it all than was prior to but im just for similar experiences me I want or? taking time read.", "In anycase it got too much and I spoke to my gp who was amazing and started me on evorel sequi for a 3 month trial. So I would say the first 4 patches have been good, I definitely seen a change in myself, I then started the conti patches, im currently on the last one of those 4, ive been brilliant until 3 days ago my anxiety has come back and its horrible. SO I have had a read of some different forums and it seems that the conti part can cause hightened anxiety. now, this didnt happen stright away and the anxiety has only just taised it head again in the last 3 days. So I dont want to complain too much as it is all better than it was prior to HRT but I guess im just looking for people with similar experiences to me, and I want to know if it got better or what? Thanks for taking the time to read. ", "Just out of interest too... In an untreated Type 1 experiencing symptoms such as hunger, what happens to blood sugar levels. Do they just rise and rise? For example, given a typical day of carb laden breakfast, lunch and dinner and snacks, would you expect the BG levels to just go out of control over a short time (mmol/l into the teens and beyond? )....", "Anyone else have post natal anxiety or depression? I’m on the wait list for counselling and my gp has prescribed tablets (although I’m not going to take them). Just wondering if anyone else is in the same boat and how you are coping? I’m so up and down x 😢" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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