Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use shanshanwang/finetuning-sentiment-model-5000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shanshanwang/finetuning-sentiment-model-5000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shanshanwang/finetuning-sentiment-model-5000-samples", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shanshanwang/finetuning-sentiment-model-5000-samples") model = AutoModelForSequenceClassification.from_pretrained("shanshanwang/finetuning-sentiment-model-5000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b9598c7b38e7d3bbd9711bbb17f5cf260c8e9d4e717a306f77fec788ded17e9
- Size of remote file:
- 5.24 kB
- SHA256:
- 1888618f719d623d48e17de26eca10ead8fc4a75322a5e9f5f2f71777616e6c2
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