Downloads · 30 days
0
HeatherFeist/QuanTarot
QuanTarot is a machine learning model from HeatherFeist. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
QuanTarot is a fine-tuned model designed to provide detailed and interactive tarot card readings. It leverages the google/flan-t5-base model and has been fine-tuned with custom tarot-related prompts and responses. The…
Downloads · 30 days
0
Access
Public
Updated Dec 8, 2024
Repo size
—
Likes
0
Public
Click a slice to open those files.
.csv3 MB · 100%
From the Hugging Face model README
QuanTarot is a fine-tuned model designed to provide detailed and interactive tarot card readings. It leverages the google/flan-t5-base model and has been fine-tuned with custom tarot-related prompts and responses. The model supports interpreting card spreads, combining numerology insights, and providing meaningful guidance.
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# Load the model and tokenizer
model_name = "your-username/quantarot-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Example prompt
prompt = "What does The Fool card represent in my current situation?"
inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
outputs = model.generate(inputs["input_ids"], max_new_tokens=150)
# Decode and print the result
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)