How to use ramnathv/clips-mfaq-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ramnathv/clips-mfaq-test") sentences = [ "<Q>How many models can I host on HuggingFace?", "<A>All plans come with unlimited private models and datasets.", "<A>AutoNLP is an automatic way to train and deploy state-of-the-art NLP models, seamlessly integrated with the Hugging Face ecosystem.", "<A>Based on how much training data and model variants are created, we send you a compute cost and payment link - as low as $10 per job." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use ramnathv/clips-mfaq-test with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ramnathv/clips-mfaq-test") model = AutoModel.from_pretrained("ramnathv/clips-mfaq-test", device_map="auto")
https://huggingface.co/ramnathv/clips-mfaq-test/resolve/main/sentence_bert_config.json
hf download hf://ramnathv/clips-mfaq-test/sentence_bert_config.json
curl -L -o sentence_bert_config.json https://huggingface.co/ramnathv/clips-mfaq-test/resolve/main/sentence_bert_config.json
