Downloads · 30 days
4
18% of all-time downloads
craftd_frontend_engineer
logorexen/craftd_frontend_engineer
craftd_frontend_engineer is a machine learning model from logorexen. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
A LoRA fine-tune of Qwen/Qwen2.5-Coder-3B-Instruct, trained to explain frontend engineering concepts (JavaScript, React, HTML, CSS) in a clear, teacher-style voice.
All-time downloads
22
Public
Parameters
3.1B
6.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors6.2 GB · 100%
At a glance
- License
- apache-2.0
- Model type
- qwen2
- Access
- Public
- Created
- Aug 2, 2026
- Updated
- Aug 3, 2026
- SHA
- c97b2f12
Base models
Model card
From the Hugging Face model README
CraftD Frontend Engineering Teacher
A LoRA fine-tune of Qwen/Qwen2.5-Coder-3B-Instruct, trained to explain frontend engineering concepts (JavaScript, React, HTML, CSS) in a clear, teacher-style voice.
Training data
- Scraped React documentation pages
- Scraped React source files (from the
facebook/reactGitHub repository) - A frontend-filtered subset of
HuggingFaceFW/fineweb-edu
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
model = AutoModelForCausalLM.from_pretrained("logorexen/craftd_frontend_engineer")
tokenizer = AutoTokenizer.from_pretrained("logorexen/craftd_frontend_engineer")
messages = [
{"role": "system", "content": "You are a professional Frontend Engineering Teacher."},
{"role": "user", "content": "Explain why we use React keys when rendering lists."},
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=400)
print(pipe(prompt)[0]["generated_text"])
- Type
- qwen2
- License
- apache-2.0
- Created
- Aug 2, 2026
- Updated
- Aug 3, 2026