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:
- 67d8cdc6b1f835fc1a789ea881d6879777b29cb019abd586ab98045c76c5a6f8
- Size of remote file:
- 268 MB
- SHA256:
- a23eceb9a1c536d659422d6ca19134efb1e44da0275df1487ed4f7043f174f99
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