Llama-3.2-3B-Instruct-MeditationGuide

Meditation Guide (Llama 3.2 - 3B)

This is a fine-tuned version of meta-llama/Meta-Llama-3.2-3B-Instruct, specifically adapted to generate guided meditation scripts. The model was trained on the AlbertoB12/GuidedMeditations1 dataset, a collection of diverse guided meditation texts.

The goal of this project is to provide a specialized AI tool for creating content in the wellness and mindfulness space. It can generate complete meditation scripts based on a simple prompt, focusing on themes like relaxation, anxiety relief, focus, and gratitude.

Model Description

• Base Model: meta-llama/Meta-Llama-3.2-3B-Instruct
• Language: English (en)
• Task: Text Generation, Guided Meditation Scripting
• Trained on: https://huggingface.co/datasets/AlbertoB12/GuidedMeditations1

The model excels at adopting a calm, encouraging, and guiding tone suitable for meditation. It understands instructions related to pacing, focus points (e.g., breath, body sensations), and common meditation themes.

Intended Uses & Limitations

Intended Uses

This model is designed for:

• Content Creation: Generating scripts for wellness apps, YouTube channels, or personal mindfulness practice.
• Personalization: Creating custom meditation scripts tailored to specific needs (e.g., "a 5-minute meditation for morning focus").
• Creative Assistance: A tool for mindfulness teachers and practitioners to brainstorm and develop new meditation content.

Disclaimer: This model is for informational and creative purposes only. The content it generates is not a substitute for professional medical or psychological advice, diagnosis, or treatment.

Limitations

• Narrow Domain: The model is highly specialized. It may not perform well on topics outside of meditation, mindfulness, and general wellness.
• Potential for Hallucination: Like all LLMs, it may occasionally generate text that is nonsensical or not perfectly aligned with the prompt.
• Bias: The model's output will reflect the styles and potential biases present in the GuidedMeditations1 dataset.

How to Use

To use this model, ensure you have accepted the terms of use for Llama 3.2 on the meta-llama/Meta-Llama-3.2-8B-Instruct model page. The model should be used with the Llama 3.2 chat template.

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import os

# --- Configuration ---
# Set your Hugging Face token (if the model is private or requires authentication)
# For HF Spaces, set this as a secret named HF_TOKEN
hf_token = os.getenv("HF_TOKEN") 
model_id = "AlbertoB12/Llama-3.2-3B-Instruct-MeditationGuide"

# --- Load Tokenizer and Model ---
tokenizer = AutoTokenizer.from_pretrained(model_id, token=hf_token, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    token=hf_token,
    trust_remote_code=True
)
model.eval()

# --- Prepare the Prompt ---
# Use the official chat template for Llama 3.2
messages = [
    {
        "role": "system",
        "content": "You are a helpful meditation guide. Your purpose is to generate calm, soothing, and effective guided meditation scripts based on the user's request."
    },
    {
        "role": "user",
        "content": "Write a 5-minute guided meditation script focused on releasing anxiety."
    },
]

prompt = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

# --- Generate the Response ---
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=1024,
    do_sample=True,
    temperature=0.7,
    top_p=0.95,
    eos_token_id=tokenizer.eos_token_id
)

# --- Decode and Print ---
response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
print(response)