How to use sentence-transformers/all-distilroberta-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/all-distilroberta-v1") 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]
How to use sentence-transformers/all-distilroberta-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/all-distilroberta-v1") model = AutoModelForMaskedLM.from_pretrained("sentence-transformers/all-distilroberta-v1", device_map="auto")
https://huggingface.co/sentence-transformers/all-distilroberta-v1/resolve/14e2a3f3090548596d23882845152a951333c0e3/sentence_bert_config.json
hf download hf://sentence-transformers/all-distilroberta-v1@14e2a3f3090548596d23882845152a951333c0e3/sentence_bert_config.json
curl -L -o sentence_bert_config.json https://huggingface.co/sentence-transformers/all-distilroberta-v1/resolve/14e2a3f3090548596d23882845152a951333c0e3/sentence_bert_config.json
