🦙 LLaMA3.2-1B-Instruct

pAce576/llama3.2-1b-Instruct is a 1.2 billion parameter language model based on Meta's LLaMA3 architecture. This model has been instruction-tuned for conversational and general-purpose natural language generation tasks.

🧠 Model Details

• Architecture: LLaMA3.2 (custom 1.2B variant)
• Base Model: LLaMA3-like Transformer
• Instruction Tuning: Yes
• Parameters: ~1.2 billion
• Layers: Custom, designed for efficient inference on resource-constrained environments
• Precision: fp16 supported (also tested with int8/4-bit via quantization)

📚 Intended Use

This model is intended for:

• Dialogue generation
• Instruction following
• Story writing
• Light reasoning tasks

Example usage:

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("pAce576/llama3.2-1b-Instruct")
tokenizer = AutoTokenizer.from_pretrained("pAce576/llama3.2-1b-Instruct")

#Your own generation function