Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use zboxi7/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zboxi7/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zboxi7/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zboxi7/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("zboxi7/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b57ffc93d0fef81adbd755cbe7389d41ba16b35e20aa14815259ff2d9e003db
- Size of remote file:
- 3.38 kB
- SHA256:
- b54db4a16919454e4c6e6fa661d81f6107cc7b31277aa3c46bd333816f2b7474
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