---
base_model:
- meta-llama/Meta-Llama-3-70B-Instruct
library_name: peft
---

# 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](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)
- **Method:** LoRA (Low-Rank Adaptation)
- **Framework:** PEFT
- **Language:** English
- **License:** [More Information Needed]

## Quick Start

```python
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.