puremood/llama70b-MARTZ

MARTZAI: LoRA Adapter for LLaMA 70B

MARTZAI is a LoRA fine-tuned adapter for LLaMA 70B, trained on Chris Martz's tweets to capture his unique style and insights.

Model Details

• Base model: meta-llama/Meta-Llama-3-70B-Instruct
• Method: LoRA (Low-Rank Adaptation)
• Framework: PEFT
• Language: English
• License: [More Information Needed]

Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-70B-Instruct")

# Load LoRA adapter
lora_model = PeftModel.from_pretrained(base_model, "your_hf_username/llama70b-lora-adapter")

# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-70B-Instruct")

# Generate text
input_text = "What are Chris Martz's views on inflation?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = lora_model.generate(**inputs)
print(tokenizer.decode(outputs[0]))

## Notes
Usage: Ideal for tasks requiring Chris Martz’s tone or expertise.
Limitations: This adapter inherits biases and constraints from the base model.

Developed by sw4geth. Contact via Hugging Face for questions or feedback.