Instructions to use rohitdiwane/bert-finetuned-rest-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitdiwane/bert-finetuned-rest-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rohitdiwane/bert-finetuned-rest-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rohitdiwane/bert-finetuned-rest-sentiment") model = AutoModelForSequenceClassification.from_pretrained("rohitdiwane/bert-finetuned-rest-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 325e0671d4b736b0f861199a5d8dd436c7d0dd747e6070fab004a744257f27e2
- Size of remote file:
- 4.66 kB
- SHA256:
- fa1f5736b27318f8576386cc1ffffec77ef6b8026cb9b81e63d7fef1eacb3b25
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