Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use DaisyQue/finetuning-sentiment-model-300-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaisyQue/finetuning-sentiment-model-300-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DaisyQue/finetuning-sentiment-model-300-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DaisyQue/finetuning-sentiment-model-300-samples") model = AutoModelForSequenceClassification.from_pretrained("DaisyQue/finetuning-sentiment-model-300-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7eca34fc3f56320cf35be3c974202e32b25ea27f4de3d14b8a01fb2cb422a908
- Size of remote file:
- 5.3 kB
- SHA256:
- ca035c8144bfdf665df920d0665cd88a9fc6621438c7504081970ca5b38b0439
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