Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert") model = AutoModelForSequenceClassification.from_pretrained("Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
model.safetensors
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tokenizer.json
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training_args.bin
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