Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use DuboiJ/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DuboiJ/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DuboiJ/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DuboiJ/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("DuboiJ/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9b58bf9a54d7fa2d4e7fdb267519381424806d8eaec2605c91b476830a00a97
- Size of remote file:
- 3.25 kB
- SHA256:
- 20e4e72f9f092fceeb5ceed083aafb3ca13293dfd96459bacfa89fbe3d49a0be
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