It is designed as the first release in the Lovelace family: a line of models focused on practical code generation, reasoning, and tooling, with an emphasis on long-term scalability, research cleanliness, and deployment stability.

Lovelace is developed with a research-first mindset: prioritising architectural soundness, future extensibility, and real-world usability over short-term leaderboard optimisation.

Model Family

Model	Parameters	Status
Lovelace-1-3B	3B	✅ Available
Lovelace-1-7B	7B	✅ Available
Lovelace-1-15B	15B	🚧 Planned

All models in the Lovelace family share a consistent design philosophy and are intended to be drop-in compatible with the Lovelace Code runtime and tooling stack.

Design Philosophy

Lovelace is guided by three core principles:

Engineering realism The model is expected to recognise infeasible requests, surface constraints clearly, and propose workable alternatives rather than hallucinating solutions.
Scalability over spectacle Training and design decisions prioritise long-term scale (larger models, longer contexts, multimodality) rather than short-term benchmark gains.
Tool-aligned coding intelligence Lovelace is designed to function as part of a broader coding system — not as an isolated chatbot.

Lovelace Code Library

The model is intended to be used alongside Lovelace Code, a companion library that provides:

Structured prompt interfaces for coding tasks
Execution-aware request handling
Support for long-running and multi-step code generation
Guardrails against unrealistic or non-computable requests

Ongoing work focuses on improving stability for long requests, including multi-file generation, extended reasoning chains, and iterative refinement workflows.

Capabilities

While formal benchmarks are not yet published, Lovelace-1-3B is trained and evaluated internally for:

Code generation and completion
Code explanation and refactoring
Debugging and error analysis
API and library usage reasoning
High-level system design discussion

The model is particularly tuned to respond sensibly under uncertainty, favouring correctness and clarity over speculative output.

Current Limitations

No public benchmark suite released yet
Context length stability for very long requests is still under active development
Vision-language capabilities are not yet supported

These limitations are explicitly acknowledged and form part of the near-term roadmap.

Roadmap

Planned future work includes:

Improved long-context stability in Lovelace Code
Release of the Lovelace-1-15B model
Vision support (code + visual inputs)
Transparent evaluation and benchmark reporting
Deeper tool and execution integration

Intended Use

Lovelace is designed for:

Research and experimentation in code-focused LLMs
Developer tooling and agentic coding systems
Education and structured programming assistance

It is not intended for safety-critical systems without further evaluation.

Acknowledgements

Lovelace-1-3B is based on the excellent work of the BigCode project, specifically starcoder2-3b.

The project is inspired by modern research-grade model releases, including OpenAI’s open-weight efforts and contemporary large-scale coding systems.

Licence

Please refer to the underlying base model and repository for licensing details. Additional terms may apply to the Lovelace Code library.

aayanmishra-ml/Lovelace-1-3B

Lovelace-1-3B

Overview