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Training Complete!

Model "{{ model_name }}" is ready to use

Model Statistics

Embedding Dimension
{{ config.embedding_dim }}
Training Chunks
{{ config.corpus_stats.num_chunks }}
Total Words
{{ config.corpus_stats.num_words }}
Unique Terms
{{ config.corpus_stats.num_unique_terms }}

Model Location

{{ model_dir }}
├── model.onnx (~8 MB)
└── config.json (metadata)

How to Use Your Model

# Load your custom model
from justembed.embedder import CustomEmbedder
import numpy as np

embedder = CustomEmbedder("{{ model_name }}")

# Embed documents
docs = ["your document text here"]
doc_embeddings = embedder.embed(docs)

# Embed query
query = "your search query"
query_embedding = embedder.embed_query(query)

# Compute similarity
similarities = [
    np.dot(query_embedding, doc_emb)
    for doc_emb in doc_embeddings
]

Next Steps

Create a Knowledge Base
Use your custom model when creating a new KB
Test Synonym Learning
Query with domain-specific terms to see synonym matching
Train More Models
Create specialized models for different domains
Back to Models Add KB Now