Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use abdalgader/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdalgader/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abdalgader/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abdalgader/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("abdalgader/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c576911925c40c30bf414034d0aedd01e27277b8dc011403e25cf332aa22994
- Size of remote file:
- 5.18 kB
- SHA256:
- bfd122a765fd4db6d51c5bad1ee952e6fe852ecd3e4eb8d84527d2909aaa60ea
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