Parks LLM v2 - US Parks Assistant ποΈ
A conversational AI model fine-tuned to help with US national parks, state parks, and recreation areas. This is an improved version with better training data and fixed attention mask handling.
Model Description
Parks LLM v2 is fine-tuned from microsoft/DialoGPT-medium on a curated dataset of park-related conversations. It provides helpful information about:
- π Packing and Preparation: What to bring for different park environments
- π Visit Planning: Best times to visit, crowd levels, weather considerations
- ποΈ Camping & Reservations: Booking guidance and accommodation options
- π¨βπ©βπ§βπ¦ Family Travel: Family-friendly park recommendations and activities
- π° Budget Tips: Cost-saving strategies and fee information
- π» Safety Guidance: Wildlife safety and Leave No Trace principles
- π₯Ύ Activities: Hiking, camping, and outdoor activity recommendations
Quick Start
from transformers import AutoTokenizer, AutoModelForCausalLM
# Load the model
tokenizer = AutoTokenizer.from_pretrained("ajc2195/parks-llm-v2")
model = AutoModelForCausalLM.from_pretrained("ajc2195/parks-llm-v2")
def ask_parks_assistant(question):
prompt = f"Human: {question}\nAssistant:"
inputs = tokenizer(prompt, return_tensors="pt", padding=True)
with torch.no_grad():
outputs = model.generate(
inputs['input_ids'],
attention_mask=inputs['attention_mask'],
max_new_tokens=80,
temperature=0.7,
do_sample=True,
repetition_penalty=1.2,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response.split("Assistant:")[-1].strip()
# Example usage
answer = ask_parks_assistant("What should I pack for desert parks?")
print(answer)
Pipeline Usage
from transformers import pipeline
parks_assistant = pipeline(
"text-generation",
model="ajc2195/parks-llm-v2",
tokenizer="ajc2195/parks-llm-v2"
)
response = parks_assistant(
"Human: What's the best time to visit Yellowstone?\nAssistant:",
max_new_tokens=60,
temperature=0.7,
do_sample=True,
repetition_penalty=1.2
)
Example Conversations
Q: What should I pack for Yellowstone? A: For Yellowstone, pack layers for changing weather, waterproof jacket, hiking boots, bear spray, sunscreen, hat, and warm clothes for evenings. Don't forget your camera and binoculars for wildlife viewing!
Q: When is the best time to visit Zion? A: The best time to visit Zion is spring (March-May) and fall (September-November) when temperatures are mild and crowds are smaller. Summer can be very hot, while winter may have snow at higher elevations.
Q: How do I make campground reservations? A: Make reservations at recreation.gov up to 5 months in advance. Popular campgrounds fill quickly, so book early. Some sites are first-come, first-served, arriving early in the morning is recommended.
Model Details
- Base Model: microsoft/DialoGPT-medium
- Training Data: 15 high-quality park conversation examples
- Training Method: Fine-tuning with improved hyperparameters
- Specialization: US National Parks and recreation areas
- Version: 2.0 (improved from original parks-llm)
Improvements in v2
- β Fixed attention mask warnings
- β Better training data diversity
- β Improved repetition penalty
- β Proper pad token handling
- β Enhanced generation parameters
Usage Tips
- Use the conversation format: "Human: [question]\nAssistant:"
- Include
attention_mask
in generation for best results - Set
repetition_penalty=1.2
to avoid repetitive outputs - Recommended
temperature=0.7
for good balance of coherence and variety
Limitations
- Focuses primarily on US parks and recreation areas
- Provides general guidance - always verify with official park sources
- Not a substitute for real-time park information, alerts, or conditions
- Training data is limited - may not cover all park scenarios
Ethical Considerations
- This model should be used as a helpful assistant, not a replacement for official park information
- Always check current park conditions, alerts, and regulations before traveling
- Be aware that park policies and conditions change frequently
License
Apache 2.0
Citation
If you use this model, please cite:
@misc{parks-llm-v2,
title={Parks LLM v2: Conversational AI for US Parks and Recreation},
author={ajc2195},
year={2025},
url={https://huggingface.co/ajc2195/parks-llm-v2}
}
Built with β€οΈ for park enthusiasts and outdoor adventurers!
- Downloads last month
- 11