How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="muzanxdem/fine_tuned_ecl")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("muzanxdem/fine_tuned_ecl")
model = AutoModelForSequenceClassification.from_pretrained("muzanxdem/fine_tuned_ecl", device_map="auto")
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Based Model

Model = distilbert-base-uncased

Fine tuned the model from our own custom dataset

with training_args.strategy.scope():
    model = TFDistilBertForSequenceClassification.from_pretrained("distilbert-base-uncased")

trainer = TFTrainer(
    model=model,                         # the instantiated 🤗 Transformers model to be trained
    args=training_args,                  # training arguments, defined above
    train_dataset=train_dataset,         # training dataset
    eval_dataset=test_dataset             # evaluation dataset
)

trainer.train()
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