Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yhwng/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhwng/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yhwng/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yhwng/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("yhwng/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d074dabc003eeb60d83207f058e08841a1f0adb95b8333f554a5e86fe64f386a
- Size of remote file:
- 4.6 kB
- SHA256:
- 24d6ac0e1875621d1d9c92aca914de0bb8fec894720d0da9723168973929bbfa
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