Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use flowfree/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowfree/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flowfree/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flowfree/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("flowfree/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
pytorch_model.bin
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runs/Mar15_03-36-44_12ee5e4fe453/events.out.tfevents.1678851415.12ee5e4fe453.448.3
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