Instructions to use Jedida/sentence_sentiments_analysis_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jedida/sentence_sentiments_analysis_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jedida/sentence_sentiments_analysis_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jedida/sentence_sentiments_analysis_roberta") model = AutoModelForSequenceClassification.from_pretrained("Jedida/sentence_sentiments_analysis_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jedida/sentence_sentiments_analysis_roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Jedida/sentence_sentiments_analysis_roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jedida/sentence_sentiments_analysis_roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jedida/sentence_sentiments_analysis_roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 79dcd008287d43abee4a8b9edcf7e5a29b6254e69704719ccb0690614e8ace25
- Size of remote file:
- 499 MB
- SHA256:
- a5c3c6765ead16d32a24c4991d649f932b85d0820f9a5cd29a3dc96b8bc5eb7c
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