Instructions to use Sayantan2001/finetuning-sentiment-model-bert-AmazonReviews-10000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayantan2001/finetuning-sentiment-model-bert-AmazonReviews-10000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayantan2001/finetuning-sentiment-model-bert-AmazonReviews-10000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayantan2001/finetuning-sentiment-model-bert-AmazonReviews-10000-samples") model = AutoModelForSequenceClassification.from_pretrained("Sayantan2001/finetuning-sentiment-model-bert-AmazonReviews-10000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 976597d3cf814948207bd22eb3b06b56f2ce5d24922edf1d973a7622092564e6
- Size of remote file:
- 438 MB
- SHA256:
- ac7b0095fb3f3c7c709e654ef35a940d1f0d22152e3accd58e1190a2e94ad398
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