Instructions to use JanSt/albert-base-v2_mbti-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JanSt/albert-base-v2_mbti-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JanSt/albert-base-v2_mbti-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JanSt/albert-base-v2_mbti-classification") model = AutoModelForSequenceClassification.from_pretrained("JanSt/albert-base-v2_mbti-classification") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JanSt/albert-base-v2_mbti-classification")
model = AutoModelForSequenceClassification.from_pretrained("JanSt/albert-base-v2_mbti-classification")Quick Links
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Check out the documentation for more information.
picture: https://en.wikipedia.org/wiki/Myers%E2%80%93Briggs_Type_Indicator
license: mit
language:
- en
metrics:
- bertscore
pipeline_tag: text-classification
library_name: transformers
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JanSt/albert-base-v2_mbti-classification")