Instructions to use kix-intl/elon-musk-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kix-intl/elon-musk-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kix-intl/elon-musk-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kix-intl/elon-musk-detector") model = AutoModelForSequenceClassification.from_pretrained("kix-intl/elon-musk-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Elon Musk Detector (EMD)
Elon Musk Detector uses DistilBERT to classify is a tweet (or post) was made by Elon Musk or Not.
Model Details
This model uses transformers and DistilBERT to classify text, based on 2 datasets.
Model Description
- Developed by: Kokohachi
- Model type: BERT
- Language(s) (NLP): English
- License: BigScience OpenRAIL-M
- Finetuned from model: DistilBERT
Uses
This model should be used only for academic purposes, and should not be used for business purposes.
Direct Use
git clone https://huggingface.co/kix-intl/elon-musk-detector
from transformers import DistilBERTTokenizer, DistilBERTModel
Load the tokenizer
loaded_tokenizer = DistilBERTTokenizer.from_pretrained(save_directory)
Load the model
loaded_model = DistilBERTModel.from_pretrained(save_directory)
Training Details
Training Data
Elon Musk Tweets
https://www.kaggle.com/datasets/gpreda/elon-musk-tweets
Twitter Tweets Sentiment Dataset
https://www.kaggle.com/datasets/yasserh/twitter-tweets-sentiment-dataset
Training Procedure
https://huggingface.co/kix-intl/elon-musk-detector/blob/main/EMD.ipynb
Model Card Contact
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