| Property | Value |
|---|---|
| Parameter Count | 1 Billion |
| Base Model | Meta-Llama-3.2-1B |
| Training Method | LoRA Fine-tuning |
| Language | Spanish |
| License | Apache 2.0 |
| Model URL | HuggingFace/JulianVelandia |
What is Llama-3.2-1B-unal-instruct-ft-gguf?
This is a specialized Spanish language model derived from Meta's Llama-3.2-1B architecture, fine-tuned specifically on academic content from the Universidad Nacional de Colombia. The model represents a focused adaptation using LoRA (Low-Rank Adaptation) technique, trained on a comprehensive dataset of 16,700 question-answer pairs from academic theses.
Implementation Details
The model underwent a 7-hour training process on Google Colab's free GPU infrastructure, utilizing the Grade Works UNAL Dataset Instruct. This dataset was carefully curated to include academic question-answer pairs, ensuring high-quality Spanish language understanding and generation capabilities.
- Base Architecture: Meta-Llama-3.2-1B foundation model
- Fine-tuning Method: LoRA adaptation for efficient training
- Dataset Size: 16,700 QA pairs from academic sources
- Training Infrastructure: Google Colab Free GPU
- Format: Instruction-based training with prompt-completion pairs
Core Capabilities
- Spanish language text generation and comprehension
- Academic content understanding and response generation
- Question-answering based on academic materials
- Efficient performance with 1B parameter architecture
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized focus on Spanish academic content, particularly from UNAL's graduate works. The use of LoRA fine-tuning on the Llama-3.2-1B base model creates an efficient and focused adaptation for academic text processing.
Q: What are the recommended use cases?
The model is particularly well-suited for: Academic question-answering in Spanish, Processing and generating academic content, Understanding and analyzing Spanish academic texts, and Supporting educational applications requiring Spanish language capabilities.