Ollama

<img width="1548" alt="Screenshot 2024-08-06 at 8 16 44 PM" src="https://github.com/user-attachments/assets/9a53a40e-4649-4d67-8433-052a5941a5b6">

New embedding models

• BGE-M3: a large embedding model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
• BGE-Large: a large embedding model trained in english.
• Paraphrase-Multilingual: A multilingual embedding model trained on parallel data for 50+ languages.

New embedding API with batch support

Ollama now supports a new API endpoint /api/embed for embedding generation:

curl http://localhost:11434/api/embed -d '{
  "model": "all-minilm",
  "input": ["Why is the sky blue?", "Why is the grass green?"]
}'

This API endpoint supports new features:

• Batches: generate embeddings for several documents in one request
• Normalized embeddings: embeddings are now normalized, improving similarity results
• Truncation: a new truncate parameter that will error if set to false
• Metrics: responses include load_duration, total_duration and prompt_eval_count metrics

See the API documentation for more details and examples.

What's Changed

• Fixed initial slow download speeds on Windows
• NUMA support will now be autodetected by Ollama to improve performance
• Fixed issue where the /api/embed would sometimes return embedding results out of order

New Contributors

• @av made their first contribution in https://github.com/ollama/ollama/pull/6147
• @sryu1 made their first contribution in https://github.com/ollama/ollama/pull/6151
• @rick-github made their first contribution in https://github.com/ollama/ollama/pull/6154

Full Changelog: https://github.com/ollama/ollama/compare/v0.3.3...v0.3.4