Instructions to use hun3359/mdistilbertV3.1-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hun3359/mdistilbertV3.1-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hun3359/mdistilbertV3.1-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hun3359/mdistilbertV3.1-sentiment") model = AutoModelForSequenceClassification.from_pretrained("hun3359/mdistilbertV3.1-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36786e0104c5044405b1009fdff272980842aadd42453bbb782f01ee066f994c
- Size of remote file:
- 664 MB
- SHA256:
- bf12b671e861a45070e434481cf43254c40f8baa08750c050ee02b6b36b9dfe4
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