Lovelace-1-3B / README.md
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---
base_model: bigcode/starcoder2-3b
tags:
- text-generation-inference
- transformers
- unsloth
- starcoder2
license: bigcode-openrail-m
language:
- en
---
# Lovelace-1-3B
*A code-focused large language model for reliable, scalable software reasoning*
---
## Overview
**Lovelace-1-3B** is a 3-billion parameter coding-centric language model built on top of the
[`bigcode/starcoder2-3b`](https://huggingface.co/bigcode/starcoder2-3b) foundation model.
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:
1. **Engineering realism**
The model is expected to recognise infeasible requests, surface constraints clearly, and propose workable alternatives rather than hallucinating solutions.
2. **Scalability over spectacle**
Training and design decisions prioritise long-term scale (larger models, longer contexts, multimodality) rather than short-term benchmark gains.
3. **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`](https://huggingface.co/bigcode/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.