Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Cat-591/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cat-591/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cat-591/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cat-591/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("Cat-591/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7d597d95cb79f03235db661ed1f19b0238e836cb680b953582d7dfa9f19cf2a
- Size of remote file:
- 5.18 kB
- SHA256:
- 6af8824a86604a79d1d20164fc22123f536ffb352519c517a93fcab8a770deec
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