References & External Resources

📖 Official Documentation

Resource	URL	Notes
Unsloth Docs	https://unsloth.ai/	Fast LLM fine-tuning
Hugging Face Transformers	https://huggingface.co/docs/transformers	Model loading, training
PyTorch	https://pytorch.org/	Deep learning framework
LoRA Paper	https://arxiv.org/abs/2106.09685	Parameter-efficient fine-tuning
bitsandbytes	https://github.com/TimDettmers/bitsandbytes	Quantization
TRL	https://github.com/huggingface/trl	SFTTrainer
PEFT	https://github.com/huggingface/peft	LoRA adapters
datasets	https://github.com/huggingface/datasets	Data loading

📄 Research Papers / Academic Sources

Paper	Authors	Link
LoRA: Low-Rank Adaptation	Hu et al.	https://arxiv.org/abs/2106.09685

🛠️ Tools & Libraries Used

Tool	Version (if known)	URL
Unsloth	latest	https://unsloth.ai/
PyTorch	>=1.13	https://pytorch.org/
transformers	>=4.30	https://huggingface.co/docs/transformers
bitsandbytes	latest	https://github.com/TimDettmers/bitsandbytes
trl	latest	https://github.com/huggingface/trl
peft	latest	https://github.com/huggingface/peft
datasets	latest	https://github.com/huggingface/datasets

🌐 Community & Learning Resources

Resource	URL	Notes
LLM Fine-Tuning Guide	https://github.com/huggingface/trl/blob/main/examples/scripts/sft/README.md	Practical SFT examples
LoRA Tutorial	https://www.philschmid.de/fine-tune-flan-t5-peft	LoRA with PEFT
llama.cpp	https://github.com/ggml-org/llama.cpp	Local inference
LM Studio	https://lmstudio.ai/	Desktop LLM UI

Project	URL	Relevance
unsloth/gemma-3-1b-it	https://huggingface.co/unsloth/gemma-3-1b-it	Base model
google/gemma-3-1b-pt	https://huggingface.co/google/gemma-3-1b-pt	Pretrained weights
iamtarun/code_instructions_120k_alpaca	https://huggingface.co/datasets/iamtarun/code_instructions_120k_alpaca	Training data

Links verified on: 2026-04-29. External links may change over time.

Last Updated: 2026-04-29
Version: 1.0
Status: Complete