# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JonnyTaylor/bert-veg")
model = AutoModelForSequenceClassification.from_pretrained("JonnyTaylor/bert-veg")Quick Links
bert-veg
This model was trained from bert-base-uncased on a custom dataset of labelled answers to the question "Are you vegetarian or vegan?" The 4 valid answers are "vegetarain", "vegan", "false", and "unknown".
It achieves the following results on the evaluation set: ~99% accuracy after 5 epochs.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: Adam
- training_precision: float32
Training results
Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JonnyTaylor/bert-veg")