---
license: mit
license_link: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/LICENSE
base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
base_model_relation: finetune
finetuned_by: boatbomber
pipeline_tag: text-generation
tags:
- chat
- reasoning
- roblox
- luau
language:
- en
datasets:
- boatbomber/roblox-info-dump
- boatbomber/the-luau-stack
---

# R1-Distill-Qwen-1.5B-Roblox-Luau

A fine tune of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) using [boatbomber/roblox-info-dump](https://huggingface.co/datasets/boatbomber/roblox-info-dump) and [boatbomber/the-luau-stack](https://huggingface.co/datasets/boatbomber/the-luau-stack) for Roblox domain knowledge.

This is intended to be used for speculative decoding with [boatbomber/R1-Distill-Qwen-14B-Roblox-Luau](https://huggingface.co/boatbomber/R1-Distill-Qwen-14B-Roblox-Luau). It can be used standalone in memory constrained environments, but is not nearly as capable as the 14B model as it has so few weights that it cannot learn the same level of detail.

Recommended inference settings:

| Parameter | Value | Notes |
| --------- | ----- | ----- |
| System Prompt | `You are an expert Roblox developer and Luau software engineer.` | Model was fine tuned with this prompt. |
| temperature   | `0.5-0.7`  | Underlying R1 Distill uses this. I've found best results with `0.55`. |
| top_p         | `0.95` | Underlying R1 Distill uses this. |

Quantization done using [Unsloth](https://docs.unsloth.ai/).

Available quants:

| Quant | Size | Notes |
| ----- | ---- | ----- |
| F16 | 3.56GB | Retains 100% accuracy. Slow and memory hungry. |
| Q8_O | 1.89GB | High resource use, but generally acceptable. Use when accuracy is crucial. |
| Q6_K | 1.46GB | Uses Q6_K for all tensors. Good for high end GPUs. |
| Q5_K_M | 1.29GB | **Recommended.** Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K |
| Q4_K_M | 1.12GB | **Recommended.** Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K |
| Q3_K_M | 0.92GB | Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K. Quality is noticeably degraded. |
