# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("j-hartmann/MindMiner")
model = AutoModelForSequenceClassification.from_pretrained("j-hartmann/MindMiner")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Hartmann, J., Bergner, A., & Hildebrand, C. (2023). MindMiner: Uncovering Linguistic Markers of Mind Perception as a New Lens to Understand Consumer-Smart Object Relationships. Journal of Consumer Psychology, Forthcoming.
You can apply MindMiner as follows:
from transformers import pipeline
model_name = "j-hartmann/MindMiner"
mindminer = pipeline(model=model_name, function_to_apply="none", device = 0)
For details, see: https://github.com/j-hartmann/MindMiner/blob/main/MindMiner.ipynb
- Downloads last month
- 11
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="j-hartmann/MindMiner")