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license: apache-2.0
language:
- en
tags:
- mistral
- alpaca
- fine-tuning
- code
- crud
- sft
- vllm
datasets:
- kramster/crud-code-tests
base_model: mistralai/Mistral-7B-Instruct-v0.2
---
# Evolve Mistral: Fine-Tuned Mistral-7B-Instruct for AI CRUD & Code Generation
This is a fine-tuned version of [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), adapted specifically for **code generation, schema-driven CRUD reasoning, and full-stack boilerplate automation**. It powers the AI agent layer behind the [Self-Revolve project](https://github.com/self-evolving-runtimes/revolve).
---
## Project Context: Self-Revolve
[Evolve Mistral](https://huggingface.co/kramster/evolve-mistral) is a fine-tuned open-source model **purpose-built for powering code generation** in the [Self-Revolve project](https://github.com/self-evolving-runtimes/revolve).
> “Instantly generate full-stack admin panels, APIs, and UIs from your database schema—powered by AI agents & LLMs.”
**Key capabilities:**
- Auto-generates CRUD APIs from DB schemas
- Generates React/MUI admin interfaces
- Supports SQL & NoSQL databases
- Works without OpenAI keys
- Open-source & self-hostable
---
## Dataset
**[`kramster/crud-code-tests`](https://huggingface.co/datasets/kramster/crud-code-tests)**
A high-quality Alpaca-style dataset focused on database and backend code generation. Each example contains:
- `instruction`
- `input`
- `output`
---
## Training Setup
| Detail | Value |
|---------------------|-------|
| Base model | `mistralai/Mistral-7B-Instruct-v0.2` |
| Dataset | `crud-code-tests` (Alpaca-style) |
| LoRA Config | r=32, alpha=16 |
| Framework | Axolotl + DeepSpeed + LoRA |
| Epochs | ~3.94 |
| Steps | 51 |
| Precision | bfloat16 |
| GPU | NVIDIA H100 80GB |
| Duration | ~10m |
| Train Loss | 0.0909 |
| Eval Loss | 0.1012 |
| FLOPs | ~347.6 trillion |
---
## Evaluation Summary
- Eval runtime: 2.84s
- Samples/sec: 2.11
- Steps/sec: 1.05
- Final learning rate: 2.93e-7
- Gradient norm: 0.064
---
## Example Usage (VLLM)
```bash
vllm-api-server \
--model kramster/evolve-mistral \
--max-model-len 64000 \
--rope-scaling '{"rope_type":"yarn","factor":4.0,"original_max_position_embeddings":32768}' \
--no-enable-prefix-caching
``` |