Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yiftach/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiftach/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yiftach/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yiftach/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("yiftach/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a040d628ecb3fbc08e20ca399b16d75ee44d318de0be29ed7e3c69cdf8f8d4a8
- Size of remote file:
- 3.38 kB
- SHA256:
- d688ae311f93c027629b9baf7ed15249afb0393872408e5e0c4eae0abff6c4e1
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