Safetensors
English
code
fullstack
algorithms
sql
devops
security
debugging
frontend
backend
lora
unsloth
amd-rocm
How to use from
Unsloth StudioInstall Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for lhordking/Shadow-coder-v3-LoRA to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for lhordking/Shadow-coder-v3-LoRA to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="lhordking/Shadow-coder-v3-LoRA",
max_seq_length=2048,
)Quick Links
Shadow-Coder v3 — Multi-Expert LoRA
Continually fine-tuned from Shadow-Coder v2, specializing in 8 coding domains.
Domains
| Domain | Examples |
|---|---|
| Fullstack Architecture | 750 |
| Algorithms (LeetCode) | 2,000 |
| SQL / Database | 2,000 |
| DevOps / Shell | 1,000 |
| Debugging / Code Review | 1,500 |
| Frontend (React/Vue) | 1,500 |
| Backend + Security | 2,000 |
| General Coding | 2,000 |
Training
- Base: Shadow-Coder v2 → merged → v3 LoRA
- GPU: AMD Radeon RX 9060 XT (ROCm 7.0)
- Method: LoRA r=16, alpha=32
- Steps: 8,000
Usage
from unsloth import FastLanguageModel
import torch
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "lhordking/Shadow-coder-v3-LoRA",
max_seq_length = 2048,
dtype = torch.bfloat16,
)
FastLanguageModel.for_inference(model)
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for lhordking/Shadow-coder-v3-LoRA to start chatting