floret

import floret import os # Create a dummy data file for training with open("data.txt", "w", encoding="utf-8") as f: f.write("This is a sample sentence for floret training.\n") f.write("Floret is great for compact word vectors.\n") f.write("More sentences for training the model.\n") # Train an unsupervised floret model # IMPORTANT: Use mode="floret" to enable floret's Bloom embeddings. # The default mode="fasttext" trains original fastText vectors. model = floret.train_unsupervised( "data.txt", model="cbow", mode="floret", hashCount=2, # Recommended for floret mode bucket=50000, # Reduced size hash table minn=3, maxn=6, dim=100, epoch=10 ) # Get a word vector vector = model.get_word_vector("floret") print(f"Vector for 'floret': {vector[:5]}...") # Print first 5 elements # Save the full model (creates a .bin file) model.save_model("vectors.bin") print("Model saved to vectors.bin") # Export the floret-specific vector table (creates a .floret file) model.save_floret_vectors("vectors.floret") print("Floret vectors saved to vectors.floret") # Clean up dummy files os.remove("data.txt") os.remove("vectors.bin") os.remove("vectors.floret")