Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use zybeich/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zybeich/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zybeich/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zybeich/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("zybeich/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1da3f585cb69e54328fa86b4028189991be6190a37e0d6a381768f157cdaa92
- Size of remote file:
- 3.64 kB
- SHA256:
- fa54886a96605f77bd6e383e7ea73d97323921d90f604427bd3e4cd8fc7cf54e
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