How to use ViktorZver/FRIDA with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ViktorZver/FRIDA") 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 ViktorZver/FRIDA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ViktorZver/FRIDA")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ViktorZver/FRIDA") model = AutoModel.from_pretrained("ViktorZver/FRIDA", device_map="auto")
https://huggingface.co/ViktorZver/FRIDA/resolve/main/tokenizer.json
hf download hf://ViktorZver/FRIDA/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/ViktorZver/FRIDA/resolve/main/tokenizer.json
